---
_id: '32243'
abstract:
- lang: eng
text: "Abstract\r\n The defining
feature of active particles is that they constantly propel themselves by locally
converting chemical energy into directed motion. This active self-propulsion prevents
them from equilibrating with their thermal environment (e.g. an aqueous solution),
thus keeping them permanently out of equilibrium. Nevertheless, the spatial dynamics
of active particles might share certain equilibrium features, in particular in
the steady state. We here focus on the time-reversal symmetry of individual spatial
trajectories as a distinct equilibrium characteristic. We investigate to what
extent the steady-state trajectories of a trapped active particle obey or break
this time-reversal symmetry. Within the framework of active Ornstein–Uhlenbeck
particles we find that the steady-state trajectories in a harmonic potential fulfill
path-wise time-reversal symmetry exactly, while this symmetry is typically broken
in anharmonic potentials."
article_number: '033216'
author:
- first_name: Lennart
full_name: Dabelow, Lennart
last_name: Dabelow
- first_name: Stefano
full_name: Bo, Stefano
last_name: Bo
- first_name: Ralf
full_name: Eichhorn, Ralf
last_name: Eichhorn
citation:
ama: 'Dabelow L, Bo S, Eichhorn R. How irreversible are steady-state trajectories
of a trapped active particle? Journal of Statistical Mechanics: Theory and
Experiment. 2021;2021(3). doi:10.1088/1742-5468/abe6fd'
apa: 'Dabelow, L., Bo, S., & Eichhorn, R. (2021). How irreversible are steady-state
trajectories of a trapped active particle? Journal of Statistical Mechanics:
Theory and Experiment, 2021(3), Article 033216. https://doi.org/10.1088/1742-5468/abe6fd'
bibtex: '@article{Dabelow_Bo_Eichhorn_2021, title={How irreversible are steady-state
trajectories of a trapped active particle?}, volume={2021}, DOI={10.1088/1742-5468/abe6fd},
number={3033216}, journal={Journal of Statistical Mechanics: Theory and Experiment},
publisher={IOP Publishing}, author={Dabelow, Lennart and Bo, Stefano and Eichhorn,
Ralf}, year={2021} }'
chicago: 'Dabelow, Lennart, Stefano Bo, and Ralf Eichhorn. “How Irreversible Are
Steady-State Trajectories of a Trapped Active Particle?” Journal of Statistical
Mechanics: Theory and Experiment 2021, no. 3 (2021). https://doi.org/10.1088/1742-5468/abe6fd.'
ieee: 'L. Dabelow, S. Bo, and R. Eichhorn, “How irreversible are steady-state trajectories
of a trapped active particle?,” Journal of Statistical Mechanics: Theory and
Experiment, vol. 2021, no. 3, Art. no. 033216, 2021, doi: 10.1088/1742-5468/abe6fd.'
mla: 'Dabelow, Lennart, et al. “How Irreversible Are Steady-State Trajectories of
a Trapped Active Particle?” Journal of Statistical Mechanics: Theory and Experiment,
vol. 2021, no. 3, 033216, IOP Publishing, 2021, doi:10.1088/1742-5468/abe6fd.'
short: 'L. Dabelow, S. Bo, R. Eichhorn, Journal of Statistical Mechanics: Theory
and Experiment 2021 (2021).'
date_created: 2022-06-28T07:27:41Z
date_updated: 2022-06-28T07:28:14Z
department:
- _id: '27'
doi: 10.1088/1742-5468/abe6fd
intvolume: ' 2021'
issue: '3'
keyword:
- Statistics
- Probability and Uncertainty
- Statistics and Probability
- Statistical and Nonlinear Physics
language:
- iso: eng
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 'Journal of Statistical Mechanics: Theory and Experiment'
publication_identifier:
issn:
- 1742-5468
publication_status: published
publisher: IOP Publishing
status: public
title: How irreversible are steady-state trajectories of a trapped active particle?
type: journal_article
user_id: '15278'
volume: 2021
year: '2021'
...
---
_id: '32244'
abstract:
- lang: eng
text: "We push the boundaries of electronic structure-based \\textit{ab-initio}\r\nmolecular
dynamics (AIMD) beyond 100 million atoms. This scale is otherwise\r\nbarely reachable
with classical force-field methods or novel neural network and\r\nmachine learning
potentials. We achieve this breakthrough by combining\r\ninnovations in linear-scaling
AIMD, efficient and approximate sparse linear\r\nalgebra, low and mixed-precision
floating-point computation on GPUs, and a\r\ncompensation scheme for the errors
introduced by numerical approximations. The\r\ncore of our work is the non-orthogonalized
local submatrix method (NOLSM),\r\nwhich scales very favorably to massively parallel
computing systems and\r\ntranslates large sparse matrix operations into highly
parallel, dense matrix\r\noperations that are ideally suited to hardware accelerators.
We demonstrate\r\nthat the NOLSM method, which is at the center point of each
AIMD step, is able\r\nto achieve a sustained performance of 324 PFLOP/s in mixed
FP16/FP32 precision\r\ncorresponding to an efficiency of 67.7% when running on
1536 NVIDIA A100 GPUs."
author:
- first_name: Robert
full_name: Schade, Robert
last_name: Schade
- first_name: Tobias
full_name: Kenter, Tobias
last_name: Kenter
- first_name: Hossam
full_name: Elgabarty, Hossam
last_name: Elgabarty
- first_name: Michael
full_name: Lass, Michael
last_name: Lass
- first_name: Ole
full_name: Schütt, Ole
last_name: Schütt
- first_name: Alfio
full_name: Lazzaro, Alfio
last_name: Lazzaro
- first_name: Hans
full_name: Pabst, Hans
last_name: Pabst
- first_name: Stephan
full_name: Mohr, Stephan
last_name: Mohr
- first_name: Jürg
full_name: Hutter, Jürg
last_name: Hutter
- first_name: Thomas D.
full_name: Kühne, Thomas D.
last_name: Kühne
- first_name: Christian
full_name: Plessl, Christian
last_name: Plessl
citation:
ama: Schade R, Kenter T, Elgabarty H, et al. Towards Electronic Structure-Based
Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.
arXiv:210408245. Published online 2021.
apa: Schade, R., Kenter, T., Elgabarty, H., Lass, M., Schütt, O., Lazzaro, A., Pabst,
H., Mohr, S., Hutter, J., Kühne, T. D., & Plessl, C. (2021). Towards Electronic
Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions
of Atoms. In arXiv:2104.08245.
bibtex: '@article{Schade_Kenter_Elgabarty_Lass_Schütt_Lazzaro_Pabst_Mohr_Hutter_Kühne_et
al._2021, title={Towards Electronic Structure-Based Ab-Initio Molecular Dynamics
Simulations with Hundreds of Millions of Atoms}, journal={arXiv:2104.08245}, author={Schade,
Robert and Kenter, Tobias and Elgabarty, Hossam and Lass, Michael and Schütt,
Ole and Lazzaro, Alfio and Pabst, Hans and Mohr, Stephan and Hutter, Jürg and
Kühne, Thomas D. and et al.}, year={2021} }'
chicago: Schade, Robert, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt,
Alfio Lazzaro, Hans Pabst, et al. “Towards Electronic Structure-Based Ab-Initio
Molecular Dynamics Simulations with Hundreds of Millions of Atoms.” ArXiv:2104.08245,
2021.
ieee: R. Schade et al., “Towards Electronic Structure-Based Ab-Initio Molecular
Dynamics Simulations with Hundreds of Millions of Atoms,” arXiv:2104.08245.
2021.
mla: Schade, Robert, et al. “Towards Electronic Structure-Based Ab-Initio Molecular
Dynamics Simulations with Hundreds of Millions of Atoms.” ArXiv:2104.08245,
2021.
short: R. Schade, T. Kenter, H. Elgabarty, M. Lass, O. Schütt, A. Lazzaro, H. Pabst,
S. Mohr, J. Hutter, T.D. Kühne, C. Plessl, ArXiv:2104.08245 (2021).
date_created: 2022-06-28T07:48:31Z
date_updated: 2022-06-28T07:49:31Z
department:
- _id: '27'
external_id:
arxiv:
- '2104.08245'
language:
- iso: eng
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: arXiv:2104.08245
status: public
title: Towards Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations
with Hundreds of Millions of Atoms
type: preprint
user_id: '15278'
year: '2021'
...
---
_id: '22220'
abstract:
- lang: eng
text: Abstract Developing resource-abundant and sustainable metal-free bifunctional
oxygen electrocatalysts is essential for the practical application of zinc–air
batteries (ZABs). 2D black phosphorus (BP) with fully exposed atoms and active
lone pair electrons can be promising for oxygen electrocatalysts, which, however,
suffers from low catalytic activity and poor electrochemical stability. Herein,
guided by density functional theory (DFT) calculations, an efficient metal-free
electrocatalyst is demonstrated via covalently bonding BP nanosheets with graphitic
carbon nitride (denoted BP-CN-c). The polarized PN covalent bonds in BP-CN-c
can efficiently regulate the electron transfer from BP to graphitic carbon nitride
and significantly promote the OOH* adsorption on phosphorus atoms. Impressively,
the oxygen evolution reaction performance of BP-CN-c (overpotential of 350 mV
at 10 mA cm−2, 90\% retention after 10 h operation) represents the state-of-the-art
among the reported BP-based metal-free catalysts. Additionally, BP-CN-c exhibits
a small half-wave overpotential of 390 mV for oxygen reduction reaction, representing
the first bifunctional BP-based metal-free oxygen catalyst. Moreover, ZABs are
assembled incorporating BP-CN-c cathodes, delivering a substantially higher peak
power density (168.3 mW cm−2) than the Pt/C+RuO2-based ZABs (101.3 mW cm−2). The
acquired insights into interfacial covalent bonds pave the way for the rational
design of new and affordable metal-free catalysts.
author:
- first_name: Xia
full_name: Wang, Xia
last_name: Wang
- first_name: Ramya
full_name: Kormath Madam Raghupathy, Ramya
id: '71692'
last_name: Kormath Madam Raghupathy
orcid: https://orcid.org/0000-0003-4667-9744
- first_name: Christine Joy
full_name: Querebillo, Christine Joy
last_name: Querebillo
- first_name: Zhongquan
full_name: Liao, Zhongquan
last_name: Liao
- first_name: Dongqi
full_name: Li, Dongqi
last_name: Li
- first_name: Kui
full_name: Lin, Kui
last_name: Lin
- first_name: Martin
full_name: Hantusch, Martin
last_name: Hantusch
- first_name: Zdeněk
full_name: Sofer, Zdeněk
last_name: Sofer
- first_name: Baohua
full_name: Li, Baohua
last_name: Li
- first_name: Ehrenfried
full_name: Zschech, Ehrenfried
last_name: Zschech
- first_name: Inez M.
full_name: Weidinger, Inez M.
last_name: Weidinger
- first_name: Thomas
full_name: Kühne, Thomas
id: '49079'
last_name: Kühne
- first_name: Hossein
full_name: Mirhosseini, Hossein
id: '71051'
last_name: Mirhosseini
orcid: 0000-0001-6179-1545
- first_name: Minghao
full_name: Yu, Minghao
last_name: Yu
- first_name: Xinliang
full_name: Feng, Xinliang
last_name: Feng
citation:
ama: Wang X, Kormath Madam Raghupathy R, Querebillo CJ, et al. Interfacial Covalent
Bonds Regulated Electron-Deficient 2D Black Phosphorus for Electrocatalytic Oxygen
Reactions. Advanced Materials. 2021;33(20):2008752. doi:https://doi.org/10.1002/adma.202008752
apa: Wang, X., Kormath Madam Raghupathy, R., Querebillo, C. J., Liao, Z., Li, D.,
Lin, K., Hantusch, M., Sofer, Z., Li, B., Zschech, E., Weidinger, I. M., Kühne,
T., Mirhosseini, H., Yu, M., & Feng, X. (2021). Interfacial Covalent Bonds
Regulated Electron-Deficient 2D Black Phosphorus for Electrocatalytic Oxygen Reactions.
Advanced Materials, 33(20), 2008752. https://doi.org/10.1002/adma.202008752
bibtex: '@article{Wang_Kormath Madam Raghupathy_Querebillo_Liao_Li_Lin_Hantusch_Sofer_Li_Zschech_et
al._2021, title={Interfacial Covalent Bonds Regulated Electron-Deficient 2D Black
Phosphorus for Electrocatalytic Oxygen Reactions}, volume={33}, DOI={https://doi.org/10.1002/adma.202008752},
number={20}, journal={Advanced Materials}, author={Wang, Xia and Kormath Madam
Raghupathy, Ramya and Querebillo, Christine Joy and Liao, Zhongquan and Li, Dongqi
and Lin, Kui and Hantusch, Martin and Sofer, Zdeněk and Li, Baohua and Zschech,
Ehrenfried and et al.}, year={2021}, pages={2008752} }'
chicago: 'Wang, Xia, Ramya Kormath Madam Raghupathy, Christine Joy Querebillo, Zhongquan
Liao, Dongqi Li, Kui Lin, Martin Hantusch, et al. “Interfacial Covalent Bonds
Regulated Electron-Deficient 2D Black Phosphorus for Electrocatalytic Oxygen Reactions.”
Advanced Materials 33, no. 20 (2021): 2008752. https://doi.org/10.1002/adma.202008752.'
ieee: 'X. Wang et al., “Interfacial Covalent Bonds Regulated Electron-Deficient
2D Black Phosphorus for Electrocatalytic Oxygen Reactions,” Advanced Materials,
vol. 33, no. 20, p. 2008752, 2021, doi: https://doi.org/10.1002/adma.202008752.'
mla: Wang, Xia, et al. “Interfacial Covalent Bonds Regulated Electron-Deficient
2D Black Phosphorus for Electrocatalytic Oxygen Reactions.” Advanced Materials,
vol. 33, no. 20, 2021, p. 2008752, doi:https://doi.org/10.1002/adma.202008752.
short: X. Wang, R. Kormath Madam Raghupathy, C.J. Querebillo, Z. Liao, D. Li, K.
Lin, M. Hantusch, Z. Sofer, B. Li, E. Zschech, I.M. Weidinger, T. Kühne, H. Mirhosseini,
M. Yu, X. Feng, Advanced Materials 33 (2021) 2008752.
date_created: 2021-05-21T12:38:41Z
date_updated: 2022-07-21T09:25:33Z
department:
- _id: '304'
doi: https://doi.org/10.1002/adma.202008752
intvolume: ' 33'
issue: '20'
keyword:
- 2D materials
- bifunctional oxygen electrocatalysts
- black phosphorus
- oxygen evolution reaction
- zinc–air batteries
language:
- iso: eng
page: '2008752'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Advanced Materials
status: public
title: Interfacial Covalent Bonds Regulated Electron-Deficient 2D Black Phosphorus
for Electrocatalytic Oxygen Reactions
type: journal_article
user_id: '71051'
volume: 33
year: '2021'
...
---
_id: '29700'
abstract:
- lang: eng
text: We have carried out an extensive search for stable polymorphs of carbon nitride
with C3N5 stoichiometry using the minima hopping method. Contrary to the widely
held opinion that stacked{,} planar{,} graphite-like structures are energetically
the most stable carbon nitride polymorphs for various nitrogen contents{,} we
find that this does not apply for nitrogen-rich materials owing to the high abundance
of N–N bonds. In fact{,} our results disclose novel morphologies with moieties
not previously considered for C3N5. We demonstrate that nitrogen-rich compounds
crystallize in a large variety of different structures due to particular characteristics
of their energy landscapes. The newly found low-energy structures of C3N5 have
band gaps within good agreement with the values measured in experimental studies.
author:
- first_name: Alireza
full_name: Ghasemi, Alireza
id: '77282'
last_name: Ghasemi
- first_name: Hossein
full_name: Mirhosseini, Hossein
id: '71051'
last_name: Mirhosseini
orcid: 0000-0001-6179-1545
- first_name: Thomas
full_name: Kühne, Thomas
id: '49079'
last_name: Kühne
citation:
ama: 'Ghasemi A, Mirhosseini H, Kühne T. Thermodynamically stable polymorphs of
nitrogen-rich carbon nitrides: a C3N5 study. Phys Chem Chem Phys. 2021;23:6422-6432.
doi:10.1039/D0CP06185A'
apa: 'Ghasemi, A., Mirhosseini, H., & Kühne, T. (2021). Thermodynamically stable
polymorphs of nitrogen-rich carbon nitrides: a C3N5 study. Phys. Chem. Chem.
Phys., 23, 6422–6432. https://doi.org/10.1039/D0CP06185A'
bibtex: '@article{Ghasemi_Mirhosseini_Kühne_2021, title={Thermodynamically stable
polymorphs of nitrogen-rich carbon nitrides: a C3N5 study}, volume={23}, DOI={10.1039/D0CP06185A}, journal={Phys.
Chem. Chem. Phys.}, publisher={The Royal Society of Chemistry}, author={Ghasemi,
Alireza and Mirhosseini, Hossein and Kühne, Thomas}, year={2021}, pages={6422–6432}
}'
chicago: 'Ghasemi, Alireza, Hossein Mirhosseini, and Thomas Kühne. “Thermodynamically
Stable Polymorphs of Nitrogen-Rich Carbon Nitrides: A C3N5 Study.” Phys. Chem.
Chem. Phys. 23 (2021): 6422–32. https://doi.org/10.1039/D0CP06185A.'
ieee: 'A. Ghasemi, H. Mirhosseini, and T. Kühne, “Thermodynamically stable polymorphs
of nitrogen-rich carbon nitrides: a C3N5 study,” Phys. Chem. Chem. Phys.,
vol. 23, pp. 6422–6432, 2021, doi: 10.1039/D0CP06185A.'
mla: 'Ghasemi, Alireza, et al. “Thermodynamically Stable Polymorphs of Nitrogen-Rich
Carbon Nitrides: A C3N5 Study.” Phys. Chem. Chem. Phys., vol. 23, The Royal
Society of Chemistry, 2021, pp. 6422–32, doi:10.1039/D0CP06185A.'
short: A. Ghasemi, H. Mirhosseini, T. Kühne, Phys. Chem. Chem. Phys. 23 (2021) 6422–6432.
date_created: 2022-01-31T11:00:05Z
date_updated: 2022-07-21T09:26:33Z
department:
- _id: '304'
doi: 10.1039/D0CP06185A
intvolume: ' 23'
language:
- iso: eng
page: 6422-6432
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Phys. Chem. Chem. Phys.
publisher: The Royal Society of Chemistry
status: public
title: 'Thermodynamically stable polymorphs of nitrogen-rich carbon nitrides: a C3N5
study'
type: journal_article
user_id: '71051'
volume: 23
year: '2021'
...
---
_id: '16294'
abstract:
- lang: eng
text: "Model predictive control is a prominent approach to construct a feedback\r\ncontrol
loop for dynamical systems. Due to real-time constraints, the major\r\nchallenge
in MPC is to solve model-based optimal control problems in a very\r\nshort amount
of time. For linear-quadratic problems, Bemporad et al. have\r\nproposed an explicit
formulation where the underlying optimization problems are\r\nsolved a priori
in an offline phase. In this article, we present an extension\r\nof this concept
in two significant ways. We consider nonlinear problems and -\r\nmore importantly
- problems with multiple conflicting objective functions. In\r\nthe offline phase,
we build a library of Pareto optimal solutions from which we\r\nthen obtain a
valid compromise solution in the online phase according to a\r\ndecision maker's
preference. Since the standard multi-parametric programming\r\napproach is no
longer valid in this situation, we instead use interpolation\r\nbetween different
entries of the library. To reduce the number of problems that\r\nhave to be solved
in the offline phase, we exploit symmetries in the dynamical\r\nsystem and the
corresponding multiobjective optimal control problem. The\r\nresults are verified
using two different examples from autonomous driving."
author:
- first_name: Sina
full_name: Ober-Blöbaum, Sina
id: '16494'
last_name: Ober-Blöbaum
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
citation:
ama: Ober-Blöbaum S, Peitz S. Explicit multiobjective model predictive control for
nonlinear systems with symmetries. International Journal of Robust and Nonlinear
Control. 2021;31(2):380-403. doi:10.1002/rnc.5281
apa: Ober-Blöbaum, S., & Peitz, S. (2021). Explicit multiobjective model predictive
control for nonlinear systems with symmetries. International Journal of Robust
and Nonlinear Control, 31(2), 380–403. https://doi.org/10.1002/rnc.5281
bibtex: '@article{Ober-Blöbaum_Peitz_2021, title={Explicit multiobjective model
predictive control for nonlinear systems with symmetries}, volume={31(2)}, DOI={10.1002/rnc.5281}, journal={International
Journal of Robust and Nonlinear Control}, author={Ober-Blöbaum, Sina and Peitz,
Sebastian}, year={2021}, pages={380–403} }'
chicago: 'Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model
Predictive Control for Nonlinear Systems with Symmetries.” International Journal
of Robust and Nonlinear Control 31(2) (2021): 380–403. https://doi.org/10.1002/rnc.5281.'
ieee: 'S. Ober-Blöbaum and S. Peitz, “Explicit multiobjective model predictive control
for nonlinear systems with symmetries,” International Journal of Robust and
Nonlinear Control, vol. 31(2), pp. 380–403, 2021, doi: 10.1002/rnc.5281.'
mla: Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model Predictive
Control for Nonlinear Systems with Symmetries.” International Journal of Robust
and Nonlinear Control, vol. 31(2), 2021, pp. 380–403, doi:10.1002/rnc.5281.
short: S. Ober-Blöbaum, S. Peitz, International Journal of Robust and Nonlinear
Control 31(2) (2021) 380–403.
date_created: 2020-03-13T12:44:36Z
date_updated: 2022-01-24T13:27:50Z
department:
- _id: '101'
doi: 10.1002/rnc.5281
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.5281
oa: '1'
page: 380-403
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: International Journal of Robust and Nonlinear Control
status: public
title: Explicit multiobjective model predictive control for nonlinear systems with
symmetries
type: journal_article
user_id: '15694'
volume: 31(2)
year: '2021'
...
---
_id: '29699'
author:
- first_name: S. Alireza
full_name: Ghasemi, S. Alireza
last_name: Ghasemi
- first_name: Thomas D.
full_name: Kühne, Thomas D.
last_name: Kühne
citation:
ama: Ghasemi SA, Kühne TD. Artificial neural networks for the kinetic energy functional
of non-interacting fermions. The Journal of Chemical Physics. 2021;154(7):074107.
doi:10.1063/5.0037319
apa: Ghasemi, S. A., & Kühne, T. D. (2021). Artificial neural networks for the
kinetic energy functional of non-interacting fermions. The Journal of Chemical
Physics, 154(7), 074107. https://doi.org/10.1063/5.0037319
bibtex: '@article{Ghasemi_Kühne_2021, title={Artificial neural networks for the
kinetic energy functional of non-interacting fermions}, volume={154}, DOI={10.1063/5.0037319}, number={7}, journal={The
Journal of Chemical Physics}, author={Ghasemi, S. Alireza and Kühne, Thomas D.},
year={2021}, pages={074107} }'
chicago: 'Ghasemi, S. Alireza, and Thomas D. Kühne. “Artificial Neural Networks
for the Kinetic Energy Functional of Non-Interacting Fermions.” The Journal
of Chemical Physics 154, no. 7 (2021): 074107. https://doi.org/10.1063/5.0037319.'
ieee: 'S. A. Ghasemi and T. D. Kühne, “Artificial neural networks for the kinetic
energy functional of non-interacting fermions,” The Journal of Chemical Physics,
vol. 154, no. 7, p. 074107, 2021, doi: 10.1063/5.0037319.'
mla: Ghasemi, S. Alireza, and Thomas D. Kühne. “Artificial Neural Networks for the
Kinetic Energy Functional of Non-Interacting Fermions.” The Journal of Chemical
Physics, vol. 154, no. 7, 2021, p. 074107, doi:10.1063/5.0037319.
short: S.A. Ghasemi, T.D. Kühne, The Journal of Chemical Physics 154 (2021) 074107.
date_created: 2022-01-31T10:59:01Z
date_updated: 2022-01-31T10:59:48Z
department:
- _id: '304'
doi: 10.1063/5.0037319
intvolume: ' 154'
issue: '7'
language:
- iso: eng
page: '074107'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: The Journal of Chemical Physics
status: public
title: Artificial neural networks for the kinetic energy functional of non-interacting
fermions
type: journal_article
user_id: '71692'
volume: 154
year: '2021'
...
---
_id: '25295'
author:
- first_name: Timon
full_name: Gurcke, Timon
id: '52174'
last_name: Gurcke
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Gurcke T, Alshomary M, Wachsmuth H. Assessing the Sufficiency of Arguments
through Conclusion Generation. In: Proceedings of the 8th Workshop on Argument
Mining. ; 2021:67-77.'
apa: Gurcke, T., Alshomary, M., & Wachsmuth, H. (2021). Assessing the Sufficiency
of Arguments through Conclusion Generation. Proceedings of the 8th Workshop
on Argument Mining, 67–77.
bibtex: '@inproceedings{Gurcke_Alshomary_Wachsmuth_2021, title={Assessing the Sufficiency
of Arguments through Conclusion Generation}, booktitle={Proceedings of the 8th
Workshop on Argument Mining}, author={Gurcke, Timon and Alshomary, Milad and Wachsmuth,
Henning}, year={2021}, pages={67–77} }'
chicago: Gurcke, Timon, Milad Alshomary, and Henning Wachsmuth. “Assessing the Sufficiency
of Arguments through Conclusion Generation.” In Proceedings of the 8th Workshop
on Argument Mining, 67–77, 2021.
ieee: T. Gurcke, M. Alshomary, and H. Wachsmuth, “Assessing the Sufficiency of Arguments
through Conclusion Generation,” in Proceedings of the 8th Workshop on Argument
Mining, 2021, pp. 67–77.
mla: Gurcke, Timon, et al. “Assessing the Sufficiency of Arguments through Conclusion
Generation.” Proceedings of the 8th Workshop on Argument Mining, 2021,
pp. 67–77.
short: 'T. Gurcke, M. Alshomary, H. Wachsmuth, in: Proceedings of the 8th Workshop
on Argument Mining, 2021, pp. 67–77.'
date_created: 2021-10-04T12:38:02Z
date_updated: 2022-05-06T08:48:51Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.argmining-1.7.pdf
page: 67 - 77
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 8th Workshop on Argument Mining
status: public
title: Assessing the Sufficiency of Arguments through Conclusion Generation
type: conference
user_id: '52174'
year: '2021'
...
---
_id: '21198'
author:
- first_name: Jonas Manuel
full_name: Hanselle, Jonas Manuel
id: '43980'
last_name: Hanselle
orcid: 0000-0002-1231-4985
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Superset
Learning: Constructing Algorithm Selectors from Imprecise Performance Data. Published
online 2021.'
apa: 'Hanselle, J. M., Tornede, A., Wever, M. D., & Hüllermeier, E. (2021).
Algorithm Selection as Superset Learning: Constructing Algorithm Selectors
from Imprecise Performance Data. The 25th Pacific-Asia Conference on Knowledge
Discovery and Data Mining (PAKDD-2021), Delhi, India.'
bibtex: '@article{Hanselle_Tornede_Wever_Hüllermeier_2021, series={PAKDD}, title={Algorithm
Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise
Performance Data}, author={Hanselle, Jonas Manuel and Tornede, Alexander and Wever,
Marcel Dominik and Hüllermeier, Eyke}, year={2021}, collection={PAKDD} }'
chicago: 'Hanselle, Jonas Manuel, Alexander Tornede, Marcel Dominik Wever, and Eyke
Hüllermeier. “Algorithm Selection as Superset Learning: Constructing Algorithm
Selectors from Imprecise Performance Data.” PAKDD, 2021.'
ieee: 'J. M. Hanselle, A. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection
as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance
Data.” 2021.'
mla: 'Hanselle, Jonas Manuel, et al. Algorithm Selection as Superset Learning:
Constructing Algorithm Selectors from Imprecise Performance Data. 2021.'
short: J.M. Hanselle, A. Tornede, M.D. Wever, E. Hüllermeier, (2021).
conference:
end_date: 2021-05-14
location: Delhi, India
name: The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021)
start_date: 2021-05-11
date_created: 2021-02-09T09:30:14Z
date_updated: 2022-08-24T12:49:06Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
series_title: PAKDD
status: public
title: 'Algorithm Selection as Superset Learning: Constructing Algorithm Selectors
from Imprecise Performance Data'
type: conference
user_id: '38209'
year: '2021'
...
---
_id: '21502'
abstract:
- lang: ger
text: Die vollständige Beschreibung fluiddynamischer und akustischer Vorgänge setzt
voraus, dass die Eigenschaften des Fluids hinlänglich bekannt sind.Während Fluidkenngrößen,
wie etwa die Schallgeschwindigkeit oder die Scherviskosität, für viele Flüssigkeiten
über weite Bereiche des thermodynamischen Zustandsraums bekannt sind, existieren
für die Volumenviskosität nur eine geringe Anzahl Messdaten.In dieser Arbeit wird
daher ein Messverfahren zur selektiven Bestimmung der Volumenviskosität von Flüssigkeiten,
basierend auf der Absorption von Ultraschallwellen, entwickelt und realisiert.Schwerpunkte
bilden dabei der simulationsgestützte Entwurf von Algorithmen zur Auswertung der
Messsignale sowie die Analyse und Weiterentwicklung einer Messanordnung, basierend
auf dem Puls-Echo-Verfahren. Neben der Absorption im Fluid treten dabei weitere
Effekte (zum Beispiel Beugung oder unvollständige Reflexion) auf, die das akustische
Signal schwächen oder anderweitig beeinflussen. Die Entwicklung von Verfahren
zur Trennung dieser Effekte von der akustischen Absorption bildet daher einen
weiteren Schwerpunkt dieser Arbeit.Abschließend wird die Volumenviskosität aus
der gemessenen akustischen Absorption für unterschiedliche Fluide in verschiedenen
thermodynamischen Zuständen unter Zuhilfenahme anderer bekannter Fluidkenngrößen
bestimmt sowie eine Unsicherheitsbetrachtung durchgeführt.
- lang: eng
text: The prerequisite for a complete description of fluid dynamic and acoustic
processes is that all properties of the fluid are known.While fluid parameters
such as the speed of sound or the shear viscosity are known for many liquids over
a wide range of thermodynamic states, only limited measurement data exist for
the bulk viscosity.In this thesis, a measurement method for the selective determination
of the bulk viscosity of liquids, based on the absorption of ultrasonic waves,
is developed and implemented.The focus is on the simulation-driven design of algorithms
for processing the measurement signals as well as the analysis and further development
of a measurement set-up based on the pulse-echo method.In addition to absorption
in the fluid, there are other effects (for example diffraction or incomplete reflection)
that weaken or otherwise influence the acoustic signal.Therefore, the development
of procedures to separate these effects from acoustic absorption is another focus
of this work.The bulk viscosity is determined from the measured acoustic absorption
for different fluids in different thermodynamic states. An uncertainty analysis
of the measured quantities concludes this thesis.
author:
- first_name: Leander
full_name: Claes, Leander
id: '11829'
last_name: Claes
orcid: 0000-0002-4393-268X
citation:
ama: Claes L. Messverfahren für die akustische Absorption in reinen Fluiden zur
Bestimmung der Volumenviskosität. Universiät Paderborn; 2021. doi:10.17619/UNIPB/1-1104
apa: Claes, L. (2021). Messverfahren für die akustische Absorption in reinen
Fluiden zur Bestimmung der Volumenviskosität. Universiät Paderborn. https://doi.org/10.17619/UNIPB/1-1104
bibtex: '@book{Claes_2021, title={Messverfahren für die akustische Absorption in
reinen Fluiden zur Bestimmung der Volumenviskosität}, DOI={10.17619/UNIPB/1-1104},
publisher={Universiät Paderborn}, author={Claes, Leander}, year={2021} }'
chicago: Claes, Leander. Messverfahren für die akustische Absorption in reinen
Fluiden zur Bestimmung der Volumenviskosität. Universiät Paderborn, 2021.
https://doi.org/10.17619/UNIPB/1-1104.
ieee: L. Claes, Messverfahren für die akustische Absorption in reinen Fluiden
zur Bestimmung der Volumenviskosität. Universiät Paderborn, 2021.
mla: Claes, Leander. Messverfahren für die akustische Absorption in reinen Fluiden
zur Bestimmung der Volumenviskosität. Universiät Paderborn, 2021, doi:10.17619/UNIPB/1-1104.
short: L. Claes, Messverfahren für die akustische Absorption in reinen Fluiden zur
Bestimmung der Volumenviskosität, Universiät Paderborn, 2021.
date_created: 2021-03-15T13:56:04Z
date_updated: 2022-09-06T07:08:31Z
department:
- _id: '49'
doi: 10.17619/UNIPB/1-1104
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://digital.ub.uni-paderborn.de/doi/10.17619/UNIPB/1-1104
oa: '1'
page: '223'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publisher: Universiät Paderborn
status: public
supervisor:
- first_name: Bernd
full_name: Henning, Bernd
id: '213'
last_name: Henning
- first_name: Jadran
full_name: Vrabec, Jadran
last_name: Vrabec
title: Messverfahren für die akustische Absorption in reinen Fluiden zur Bestimmung
der Volumenviskosität
type: dissertation
user_id: '11829'
year: '2021'
...
---
_id: '29294'
author:
- first_name: Tobias
full_name: Nickchen, Tobias
id: '27340'
last_name: Nickchen
orcid: 0000-0001-8958-9330
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data
for Image Recognition of Additively Manufactured Parts. In: 2021 IEEE Winter
Conference on Applications of Computer Vision (WACV). IEEE; 2021. doi:10.1109/wacv48630.2021.00204'
apa: Nickchen, T., Heindorf, S., & Engels, G. (2021). Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts. 2021
IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv48630.2021.00204
bibtex: '@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={10.1109/wacv48630.2021.00204},
booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)},
publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor},
year={2021} }'
chicago: Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically
Sound Training Data for Image Recognition of Additively Manufactured Parts.” In
2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
IEEE, 2021. https://doi.org/10.1109/wacv48630.2021.00204.
ieee: 'T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training
Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: 10.1109/wacv48630.2021.00204.'
mla: Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image
Recognition of Additively Manufactured Parts.” 2021 IEEE Winter Conference
on Applications of Computer Vision (WACV), IEEE, 2021, doi:10.1109/wacv48630.2021.00204.
short: 'T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on
Applications of Computer Vision (WACV), IEEE, 2021.'
date_created: 2022-01-12T10:31:42Z
date_updated: 2022-10-17T15:07:38Z
department:
- _id: '66'
- _id: '574'
doi: 10.1109/wacv48630.2021.00204
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openaccess.thecvf.com/content/WACV2021/papers/Nickchen_Generating_Physically_Sound_Training_Data_for_Image_Recognition_of_Additively_WACV_2021_paper.pdf
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
publication_status: published
publisher: IEEE
status: public
title: Generating Physically Sound Training Data for Image Recognition of Additively
Manufactured Parts
type: conference
user_id: '11871'
year: '2021'
...
---
_id: '24000'
author:
- first_name: Jens
full_name: Heitkaemper, Jens
id: '27643'
last_name: Heitkaemper
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Valentin
full_name: Ion, Valentin
last_name: Ion
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Heitkaemper J, Schmalenstroeer J, Ion V, Haeb-Umbach R. A Database for Research
on Detection and Enhancement of Speech Transmitted over HF links. In: Speech
Communication; 14th ITG-Symposium. ; 2021:1-5.'
apa: Heitkaemper, J., Schmalenstroeer, J., Ion, V., & Haeb-Umbach, R. (2021).
A Database for Research on Detection and Enhancement of Speech Transmitted over
HF links. Speech Communication; 14th ITG-Symposium, 1–5.
bibtex: '@inproceedings{Heitkaemper_Schmalenstroeer_Ion_Haeb-Umbach_2021, title={A
Database for Research on Detection and Enhancement of Speech Transmitted over
HF links}, booktitle={Speech Communication; 14th ITG-Symposium}, author={Heitkaemper,
Jens and Schmalenstroeer, Joerg and Ion, Valentin and Haeb-Umbach, Reinhold},
year={2021}, pages={1–5} }'
chicago: Heitkaemper, Jens, Joerg Schmalenstroeer, Valentin Ion, and Reinhold Haeb-Umbach.
“A Database for Research on Detection and Enhancement of Speech Transmitted over
HF Links.” In Speech Communication; 14th ITG-Symposium, 1–5, 2021.
ieee: J. Heitkaemper, J. Schmalenstroeer, V. Ion, and R. Haeb-Umbach, “A Database
for Research on Detection and Enhancement of Speech Transmitted over HF links,”
in Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
mla: Heitkaemper, Jens, et al. “A Database for Research on Detection and Enhancement
of Speech Transmitted over HF Links.” Speech Communication; 14th ITG-Symposium,
2021, pp. 1–5.
short: 'J. Heitkaemper, J. Schmalenstroeer, V. Ion, R. Haeb-Umbach, in: Speech Communication;
14th ITG-Symposium, 2021, pp. 1–5.'
date_created: 2021-09-09T08:41:25Z
date_updated: 2023-10-26T08:06:57Z
department:
- _id: '54'
language:
- iso: eng
page: 1-5
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Speech Communication; 14th ITG-Symposium
quality_controlled: '1'
status: public
title: A Database for Research on Detection and Enhancement of Speech Transmitted
over HF links
type: conference
user_id: '460'
year: '2021'
...
---
_id: '28259'
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Wangyou
full_name: Zhang, Wangyou
last_name: Zhang
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Tsubasa
full_name: Ochiai, Tsubasa
last_name: Ochiai
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Naoyuki
full_name: Kamo, Naoyuki
last_name: Kamo
- first_name: Yanmin
full_name: Qian, Yanmin
last_name: Qian
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Boeddeker C, Zhang W, Nakatani T, et al. Convolutive Transfer Function Invariant
SDR Training Criteria for Multi-Channel Reverberant Speech Separation. In: ICASSP
2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP). ; 2021. doi:10.1109/icassp39728.2021.9414661'
apa: Boeddeker, C., Zhang, W., Nakatani, T., Kinoshita, K., Ochiai, T., Delcroix,
M., Kamo, N., Qian, Y., & Haeb-Umbach, R. (2021). Convolutive Transfer Function
Invariant SDR Training Criteria for Multi-Channel Reverberant Speech Separation.
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP). https://doi.org/10.1109/icassp39728.2021.9414661
bibtex: '@inproceedings{Boeddeker_Zhang_Nakatani_Kinoshita_Ochiai_Delcroix_Kamo_Qian_Haeb-Umbach_2021,
title={Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation}, DOI={10.1109/icassp39728.2021.9414661},
booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)}, author={Boeddeker, Christoph and Zhang, Wangyou
and Nakatani, Tomohiro and Kinoshita, Keisuke and Ochiai, Tsubasa and Delcroix,
Marc and Kamo, Naoyuki and Qian, Yanmin and Haeb-Umbach, Reinhold}, year={2021}
}'
chicago: Boeddeker, Christoph, Wangyou Zhang, Tomohiro Nakatani, Keisuke Kinoshita,
Tsubasa Ochiai, Marc Delcroix, Naoyuki Kamo, Yanmin Qian, and Reinhold Haeb-Umbach.
“Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation.” In ICASSP 2021 - 2021 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP), 2021. https://doi.org/10.1109/icassp39728.2021.9414661.
ieee: 'C. Boeddeker et al., “Convolutive Transfer Function Invariant SDR
Training Criteria for Multi-Channel Reverberant Speech Separation,” 2021, doi:
10.1109/icassp39728.2021.9414661.'
mla: Boeddeker, Christoph, et al. “Convolutive Transfer Function Invariant SDR Training
Criteria for Multi-Channel Reverberant Speech Separation.” ICASSP 2021 - 2021
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021, doi:10.1109/icassp39728.2021.9414661.
short: 'C. Boeddeker, W. Zhang, T. Nakatani, K. Kinoshita, T. Ochiai, M. Delcroix,
N. Kamo, Y. Qian, R. Haeb-Umbach, in: ICASSP 2021 - 2021 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP), 2021.'
date_created: 2021-12-03T12:00:16Z
date_updated: 2023-11-15T15:18:09Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.1109/icassp39728.2021.9414661
file:
- access_level: open_access
content_type: application/pdf
creator: cbj
date_created: 2021-12-03T12:01:20Z
date_updated: 2023-11-15T15:18:08Z
file_id: '28260'
file_name: ICASSP2021_BSSEval.pdf
file_size: 228717
relation: main_file
file_date_updated: 2023-11-15T15:18:08Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
publication_status: published
status: public
title: Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation
type: conference
user_id: '40767'
year: '2021'
...
---
_id: '29304'
abstract:
- lang: eng
text: 'In this work we address disentanglement of style and content in speech signals.
We propose a fully convolutional variational autoencoder employing two encoders:
a content encoder and a style encoder. To foster disentanglement, we propose adversarial
contrastive predictive coding. This new disentanglement method does neither need
parallel data nor any supervision. We show that the proposed technique is capable
of separating speaker and content traits into the two different representations
and show competitive speaker-content disentanglement performance compared to other
unsupervised approaches. We further demonstrate an increased robustness of the
content representation against a train-test mismatch compared to spectral features,
when used for phone recognition.'
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Michael
full_name: Kuhlmann, Michael
id: '49871'
last_name: Kuhlmann
- first_name: Tobias
full_name: Cord-Landwehr, Tobias
id: '44393'
last_name: Cord-Landwehr
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Kuhlmann M, Cord-Landwehr T, Haeb-Umbach R. Contrastive Predictive
Coding Supported Factorized Variational Autoencoder for Unsupervised Learning
of Disentangled Speech Representations. In: Proceedings of the IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP). ; 2021:3860–3864.'
apa: Ebbers, J., Kuhlmann, M., Cord-Landwehr, T., & Haeb-Umbach, R. (2021).
Contrastive Predictive Coding Supported Factorized Variational Autoencoder for
Unsupervised Learning of Disentangled Speech Representations. Proceedings of
the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
3860–3864.
bibtex: '@inproceedings{Ebbers_Kuhlmann_Cord-Landwehr_Haeb-Umbach_2021, title={Contrastive
Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised
Learning of Disentangled Speech Representations}, booktitle={Proceedings of the
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
author={Ebbers, Janek and Kuhlmann, Michael and Cord-Landwehr, Tobias and Haeb-Umbach,
Reinhold}, year={2021}, pages={3860–3864} }'
chicago: Ebbers, Janek, Michael Kuhlmann, Tobias Cord-Landwehr, and Reinhold Haeb-Umbach.
“Contrastive Predictive Coding Supported Factorized Variational Autoencoder for
Unsupervised Learning of Disentangled Speech Representations.” In Proceedings
of the IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 3860–3864, 2021.
ieee: J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, and R. Haeb-Umbach, “Contrastive
Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised
Learning of Disentangled Speech Representations,” in Proceedings of the IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021, pp. 3860–3864.
mla: Ebbers, Janek, et al. “Contrastive Predictive Coding Supported Factorized Variational
Autoencoder for Unsupervised Learning of Disentangled Speech Representations.”
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP), 2021, pp. 3860–3864.
short: 'J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, R. Haeb-Umbach, in: Proceedings
of the IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 2021, pp. 3860–3864.'
date_created: 2022-01-13T07:55:29Z
date_updated: 2023-11-22T08:29:42Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T07:56:30Z
date_updated: 2022-01-13T08:19:19Z
file_id: '29305'
file_name: Template.pdf
file_size: 236628
relation: main_file
file_date_updated: 2022-01-13T08:19:19Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 3860–3864
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
quality_controlled: '1'
status: public
title: Contrastive Predictive Coding Supported Factorized Variational Autoencoder
for Unsupervised Learning of Disentangled Speech Representations
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '26770'
abstract:
- lang: eng
text: "Automatic transcription of meetings requires handling of overlapped speech,
which calls for continuous speech separation (CSS) systems. The uPIT criterion
was proposed for utterance-level separation with neural networks and introduces
the constraint that the total number of speakers must not exceed the number of
output channels. When processing meeting-like data in a segment-wise manner, i.e.,
by separating overlapping segments independently and stitching adjacent segments
to continuous output streams, this constraint has to be fulfilled for any segment.
In this contribution, we show that this constraint can be significantly relaxed.
We propose a novel graph-based PIT criterion, which casts the assignment of utterances
to output channels in a graph coloring problem. It only requires that the number
of concurrently active speakers must not exceed the number of output channels.
As a consequence, the system can process an arbitrary number of speakers and arbitrarily
long segments and thus can handle more diverse scenarios.\r\nFurther, the stitching
algorithm for obtaining a consistent output order in neighboring segments is of
less importance and can even be eliminated completely, not the least reducing
the computational effort. Experiments on meeting-style WSJ data show improvements
in recognition performance over using the uPIT criterion. "
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Kinoshita K, Boeddeker C, Delcroix M, Haeb-Umbach R. Graph-PIT:
Generalized Permutation Invariant Training for Continuous Separation of Arbitrary
Numbers of Speakers. In: Interspeech 2021. ; 2021. doi:10.21437/interspeech.2021-1177'
apa: 'von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., & Haeb-Umbach,
R. (2021). Graph-PIT: Generalized Permutation Invariant Training for Continuous
Separation of Arbitrary Numbers of Speakers. Interspeech 2021. Interspeech.
https://doi.org/10.21437/interspeech.2021-1177'
bibtex: '@inproceedings{von Neumann_Kinoshita_Boeddeker_Delcroix_Haeb-Umbach_2021,
title={Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers}, DOI={10.21437/interspeech.2021-1177},
booktitle={Interspeech 2021}, author={von Neumann, Thilo and Kinoshita, Keisuke
and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold}, year={2021}
}'
chicago: 'Neumann, Thilo von, Keisuke Kinoshita, Christoph Boeddeker, Marc Delcroix,
and Reinhold Haeb-Umbach. “Graph-PIT: Generalized Permutation Invariant Training
for Continuous Separation of Arbitrary Numbers of Speakers.” In Interspeech
2021, 2021. https://doi.org/10.21437/interspeech.2021-1177.'
ieee: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach,
“Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers,” presented at the Interspeech, 2021, doi: 10.21437/interspeech.2021-1177.'
mla: 'von Neumann, Thilo, et al. “Graph-PIT: Generalized Permutation Invariant Training
for Continuous Separation of Arbitrary Numbers of Speakers.” Interspeech 2021,
2021, doi:10.21437/interspeech.2021-1177.'
short: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach,
in: Interspeech 2021, 2021.'
conference:
name: Interspeech
date_created: 2021-10-25T08:50:01Z
date_updated: 2023-11-15T12:14:40Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.21437/interspeech.2021-1177
file:
- access_level: open_access
content_type: video/mp4
creator: tvn
date_created: 2021-12-06T10:39:13Z
date_updated: 2021-12-06T10:48:30Z
file_id: '28327'
file_name: Interspeech 2021 voiceover-002-compressed.mp4
file_size: 9550220
relation: supplementary_material
title: Video for INTERSPEECH 2021
- access_level: open_access
content_type: application/vnd.openxmlformats-officedocument.presentationml.presentation
creator: tvn
date_created: 2021-12-06T10:47:01Z
date_updated: 2021-12-06T10:47:01Z
file_id: '28328'
file_name: Graph-PIT-poster-presentation.pptx
file_size: 1337297
relation: slides
title: Slides from INTERSPEECH 2021
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2021-12-06T10:48:21Z
date_updated: 2021-12-06T10:48:21Z
file_id: '28329'
file_name: INTERSPEECH2021_Graph_PIT.pdf
file_size: 226589
relation: main_file
file_date_updated: 2021-12-06T10:48:30Z
has_accepted_license: '1'
keyword:
- Continuous speech separation
- automatic speech recognition
- overlapped speech
- permutation invariant training
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Interspeech 2021
publication_status: published
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/fgnt/graph_pit
status: public
title: 'Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers'
type: conference
user_id: '49870'
year: '2021'
...
---
_id: '29173'
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Boeddeker C, Kinoshita K, Delcroix M, Haeb-Umbach R. Speeding
Up Permutation Invariant Training for Source Separation. In: Speech Communication;
14th ITG Conference. ; 2021.'
apa: von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., & Haeb-Umbach,
R. (2021). Speeding Up Permutation Invariant Training for Source Separation. Speech
Communication; 14th ITG Conference. Speech Communication; 14th ITG Conference,
Kiel.
bibtex: '@inproceedings{von Neumann_Boeddeker_Kinoshita_Delcroix_Haeb-Umbach_2021,
title={Speeding Up Permutation Invariant Training for Source Separation}, booktitle={Speech
Communication; 14th ITG Conference}, author={von Neumann, Thilo and Boeddeker,
Christoph and Kinoshita, Keisuke and Delcroix, Marc and Haeb-Umbach, Reinhold},
year={2021} }'
chicago: Neumann, Thilo von, Christoph Boeddeker, Keisuke Kinoshita, Marc Delcroix,
and Reinhold Haeb-Umbach. “Speeding Up Permutation Invariant Training for Source
Separation.” In Speech Communication; 14th ITG Conference, 2021.
ieee: T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, and R. Haeb-Umbach,
“Speeding Up Permutation Invariant Training for Source Separation,” presented
at the Speech Communication; 14th ITG Conference, Kiel, 2021.
mla: von Neumann, Thilo, et al. “Speeding Up Permutation Invariant Training for
Source Separation.” Speech Communication; 14th ITG Conference, 2021.
short: 'T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, R. Haeb-Umbach,
in: Speech Communication; 14th ITG Conference, 2021.'
conference:
end_date: 2021-10-01
location: Kiel
name: Speech Communication; 14th ITG Conference
start_date: 2021-09-29
date_created: 2022-01-07T10:40:56Z
date_updated: 2023-11-15T12:16:31Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2022-01-06T13:23:27Z
date_updated: 2022-01-06T13:23:27Z
file_id: '29180'
file_name: poster.pdf
file_size: 191938
relation: poster
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2022-01-07T10:42:54Z
date_updated: 2022-01-07T10:42:54Z
file_id: '29181'
file_name: ITG2021_Speeding_up_Permutation_Invariant_Training.pdf
file_size: 236670
relation: main_file
file_date_updated: 2022-01-07T10:42:54Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Speech Communication; 14th ITG Conference
quality_controlled: '1'
status: public
title: Speeding Up Permutation Invariant Training for Source Separation
type: conference
user_id: '49870'
year: '2021'
...
---
_id: '29308'
abstract:
- lang: eng
text: 'In this paper we present our system for the Detection and Classification
of Acoustic Scenes and Events (DCASE) 2021 Challenge Task 4: Sound Event Detection
and Separation in Domestic Environments, where it scored the fourth rank. Our
presented solution is an advancement of our system used in the previous edition
of the task.We use a forward-backward convolutional recurrent neural network (FBCRNN)
for tagging and pseudo labeling followed by tag-conditioned sound event detection
(SED) models which are trained using strong pseudo labels provided by the FBCRNN.
Our advancement over our earlier model is threefold. First, we introduce a strong
label loss in the objective of the FBCRNN to take advantage of the strongly labeled
synthetic data during training. Second, we perform multiple iterations of self-training
for both the FBCRNN and tag-conditioned SED models. Third, while we used only
tag-conditioned CNNs as our SED model in the previous edition we here explore
sophisticated tag-conditioned SED model architectures, namely, bidirectional CRNNs
and bidirectional convolutional transformer neural networks (CTNNs), and combine
them. With metric and class specific tuning of median filter lengths for post-processing,
our final SED model, consisting of 6 submodels (2 of each architecture), achieves
on the public evaluation set poly-phonic sound event detection scores (PSDS) of
0.455 for scenario 1 and 0.684 for scenario as well as a collar-based F1-score
of 0.596 outperforming the baselines and our model from the previous edition by
far. Source code is publicly available at https://github.com/fgnt/pb_sed.'
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Haeb-Umbach R. Self-Trained Audio Tagging and Sound Event Detection
in Domestic Environments. In: Proceedings of the 6th Detection and Classification
of Acoustic Scenes and Events 2021 Workshop (DCASE2021). ; 2021:226–230.'
apa: Ebbers, J., & Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound
Event Detection in Domestic Environments. Proceedings of the 6th Detection
and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
226–230.
bibtex: '@inproceedings{Ebbers_Haeb-Umbach_2021, place={Barcelona, Spain}, title={Self-Trained
Audio Tagging and Sound Event Detection in Domestic Environments}, booktitle={Proceedings
of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop
(DCASE2021)}, author={Ebbers, Janek and Haeb-Umbach, Reinhold}, year={2021}, pages={226–230}
}'
chicago: Ebbers, Janek, and Reinhold Haeb-Umbach. “Self-Trained Audio Tagging and
Sound Event Detection in Domestic Environments.” In Proceedings of the 6th
Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
226–230. Barcelona, Spain, 2021.
ieee: J. Ebbers and R. Haeb-Umbach, “Self-Trained Audio Tagging and Sound Event
Detection in Domestic Environments,” in Proceedings of the 6th Detection and
Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021), 2021,
pp. 226–230.
mla: Ebbers, Janek, and Reinhold Haeb-Umbach. “Self-Trained Audio Tagging and Sound
Event Detection in Domestic Environments.” Proceedings of the 6th Detection
and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
2021, pp. 226–230.
short: 'J. Ebbers, R. Haeb-Umbach, in: Proceedings of the 6th Detection and Classification
of Acoustic Scenes and Events 2021 Workshop (DCASE2021), Barcelona, Spain, 2021,
pp. 226–230.'
date_created: 2022-01-13T08:07:47Z
date_updated: 2023-11-22T08:28:32Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T08:08:54Z
date_updated: 2022-01-13T08:19:50Z
file_id: '29309'
file_name: template.pdf
file_size: 239462
relation: main_file
file_date_updated: 2022-01-13T08:19:50Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 226–230
place: Barcelona, Spain
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 6th Detection and Classification of Acoustic Scenes
and Events 2021 Workshop (DCASE2021)
publication_identifier:
isbn:
- 978-84-09-36072-7
quality_controlled: '1'
status: public
title: Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '29306'
abstract:
- lang: eng
text: Recently, there has been a rising interest in sound recognition via Acoustic
Sensor Networks to support applications such as ambient assisted living or environmental
habitat monitoring. With state-of-the-art sound recognition being dominated by
deep-learning-based approaches, there is a high demand for labeled training data.
Despite the availability of large-scale data sets such as Google's AudioSet,
acquiring training data matching a certain application environment is still often
a problem. In this paper we are concerned with human activity monitoring in a
domestic environment using an ASN consisting of multiple nodes each providing
multichannel signals. We propose a self-training based domain adaptation approach,
which only requires unlabeled data from the target environment. Here, a sound
recognition system trained on AudioSet, the teacher, generates pseudo labels for
data from the target environment on which a student network is trained. The student
can furthermore glean information about the spatial arrangement of sensors and
sound sources to further improve classification performance. It is shown that the
student significantly improves recognition performance over the pre-trained teacher
without relying on labeled data from the environment the system is deployed in.
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Moritz Curt
full_name: Keyser, Moritz Curt
last_name: Keyser
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Keyser MC, Haeb-Umbach R. Adapting Sound Recognition to A New Environment
Via Self-Training. In: Proceedings of the 29th European Signal Processing Conference
(EUSIPCO). ; 2021:1135–1139.'
apa: Ebbers, J., Keyser, M. C., & Haeb-Umbach, R. (2021). Adapting Sound Recognition
to A New Environment Via Self-Training. Proceedings of the 29th European Signal
Processing Conference (EUSIPCO), 1135–1139.
bibtex: '@inproceedings{Ebbers_Keyser_Haeb-Umbach_2021, title={Adapting Sound Recognition
to A New Environment Via Self-Training}, booktitle={Proceedings of the 29th European
Signal Processing Conference (EUSIPCO)}, author={Ebbers, Janek and Keyser, Moritz
Curt and Haeb-Umbach, Reinhold}, year={2021}, pages={1135–1139} }'
chicago: Ebbers, Janek, Moritz Curt Keyser, and Reinhold Haeb-Umbach. “Adapting
Sound Recognition to A New Environment Via Self-Training.” In Proceedings of
the 29th European Signal Processing Conference (EUSIPCO), 1135–1139, 2021.
ieee: J. Ebbers, M. C. Keyser, and R. Haeb-Umbach, “Adapting Sound Recognition to
A New Environment Via Self-Training,” in Proceedings of the 29th European Signal
Processing Conference (EUSIPCO), 2021, pp. 1135–1139.
mla: Ebbers, Janek, et al. “Adapting Sound Recognition to A New Environment Via
Self-Training.” Proceedings of the 29th European Signal Processing Conference
(EUSIPCO), 2021, pp. 1135–1139.
short: 'J. Ebbers, M.C. Keyser, R. Haeb-Umbach, in: Proceedings of the 29th European
Signal Processing Conference (EUSIPCO), 2021, pp. 1135–1139.'
date_created: 2022-01-13T08:01:21Z
date_updated: 2023-11-22T08:28:50Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T08:03:26Z
date_updated: 2022-01-13T08:19:35Z
file_id: '29307'
file_name: conference_101719.pdf
file_size: 213938
relation: main_file
file_date_updated: 2022-01-13T08:19:35Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 1135–1139
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 29th European Signal Processing Conference (EUSIPCO)
quality_controlled: '1'
status: public
title: Adapting Sound Recognition to A New Environment Via Self-Training
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '35131'
abstract:
- lang: eng
text: An FPGA accelerator for the computation of the semi-global Levenshtein distance
between a pattern and a reference text is presented. The accelerator provides
an important benefit to reduce the execution time of read-mappers used in short-read
genomic sequencing. Previous attempts to solve the same problem in FPGA use the
Myers algorithm following a column approach to compute the dynamic programming
table. We use an approach based on diagonals that allows for some resource savings
while maintaining a very high throughput of 1 alignment per clock cycle. The design
is implemented in OpenCL and tested on two FPGA accelerators. The maximum performance
obtained is 91.5 MPairs/s for 100 × 120 sequences and 47 MPairs/s for 300 × 360
sequences, the highest ever reported for this problem.
author:
- first_name: David
full_name: Castells-Rufas, David
last_name: Castells-Rufas
- first_name: Santiago
full_name: Marco-Sola, Santiago
last_name: Marco-Sola
- first_name: Quim
full_name: Aguado-Puig, Quim
last_name: Aguado-Puig
- first_name: Antonio
full_name: Espinosa-Morales, Antonio
last_name: Espinosa-Morales
- first_name: Juan Carlos
full_name: Moure, Juan Carlos
last_name: Moure
- first_name: Lluc
full_name: Alvarez, Lluc
last_name: Alvarez
- first_name: Miquel
full_name: Moreto, Miquel
last_name: Moreto
citation:
ama: 'Castells-Rufas D, Marco-Sola S, Aguado-Puig Q, et al. OpenCL-based FPGA Accelerator
for Semi-Global Approximate String Matching Using Diagonal Bit-Vectors. In: 2021
31st International Conference on Field-Programmable Logic and Applications (FPL).
IEEE; 2021. doi:10.1109/fpl53798.2021.00036'
apa: Castells-Rufas, D., Marco-Sola, S., Aguado-Puig, Q., Espinosa-Morales, A.,
Moure, J. C., Alvarez, L., & Moreto, M. (2021). OpenCL-based FPGA Accelerator
for Semi-Global Approximate String Matching Using Diagonal Bit-Vectors. 2021
31st International Conference on Field-Programmable Logic and Applications (FPL).
https://doi.org/10.1109/fpl53798.2021.00036
bibtex: '@inproceedings{Castells-Rufas_Marco-Sola_Aguado-Puig_Espinosa-Morales_Moure_Alvarez_Moreto_2021,
title={OpenCL-based FPGA Accelerator for Semi-Global Approximate String Matching
Using Diagonal Bit-Vectors}, DOI={10.1109/fpl53798.2021.00036},
booktitle={2021 31st International Conference on Field-Programmable Logic and
Applications (FPL)}, publisher={IEEE}, author={Castells-Rufas, David and Marco-Sola,
Santiago and Aguado-Puig, Quim and Espinosa-Morales, Antonio and Moure, Juan Carlos
and Alvarez, Lluc and Moreto, Miquel}, year={2021} }'
chicago: Castells-Rufas, David, Santiago Marco-Sola, Quim Aguado-Puig, Antonio Espinosa-Morales,
Juan Carlos Moure, Lluc Alvarez, and Miquel Moreto. “OpenCL-Based FPGA Accelerator
for Semi-Global Approximate String Matching Using Diagonal Bit-Vectors.” In 2021
31st International Conference on Field-Programmable Logic and Applications (FPL).
IEEE, 2021. https://doi.org/10.1109/fpl53798.2021.00036.
ieee: 'D. Castells-Rufas et al., “OpenCL-based FPGA Accelerator for Semi-Global
Approximate String Matching Using Diagonal Bit-Vectors,” 2021, doi: 10.1109/fpl53798.2021.00036.'
mla: Castells-Rufas, David, et al. “OpenCL-Based FPGA Accelerator for Semi-Global
Approximate String Matching Using Diagonal Bit-Vectors.” 2021 31st International
Conference on Field-Programmable Logic and Applications (FPL), IEEE, 2021,
doi:10.1109/fpl53798.2021.00036.
short: 'D. Castells-Rufas, S. Marco-Sola, Q. Aguado-Puig, A. Espinosa-Morales, J.C.
Moure, L. Alvarez, M. Moreto, in: 2021 31st International Conference on Field-Programmable
Logic and Applications (FPL), IEEE, 2021.'
date_created: 2023-01-03T10:05:13Z
date_updated: 2024-01-22T09:56:25Z
doi: 10.1109/fpl53798.2021.00036
keyword:
- pc2-harp-ressources
language:
- iso: eng
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 2021 31st International Conference on Field-Programmable Logic and Applications
(FPL)
publication_status: published
publisher: IEEE
quality_controlled: '1'
status: public
title: OpenCL-based FPGA Accelerator for Semi-Global Approximate String Matching Using
Diagonal Bit-Vectors
type: conference
user_id: '3145'
year: '2021'
...
---
_id: '29937'
author:
- first_name: Martin
full_name: Karp, Martin
last_name: Karp
- first_name: Artur
full_name: Podobas, Artur
last_name: Podobas
- first_name: Niclas
full_name: Jansson, Niclas
last_name: Jansson
- first_name: Tobias
full_name: Kenter, Tobias
id: '3145'
last_name: Kenter
- first_name: Christian
full_name: Plessl, Christian
id: '16153'
last_name: Plessl
orcid: 0000-0001-5728-9982
- first_name: Philipp
full_name: Schlatter, Philipp
last_name: Schlatter
- first_name: Stefano
full_name: Markidis, Stefano
last_name: Markidis
citation:
ama: 'Karp M, Podobas A, Jansson N, et al. High-Performance Spectral Element Methods
on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection.
In: 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS).
IEEE; 2021. doi:10.1109/ipdps49936.2021.00116'
apa: 'Karp, M., Podobas, A., Jansson, N., Kenter, T., Plessl, C., Schlatter, P.,
& Markidis, S. (2021). High-Performance Spectral Element Methods on Field-Programmable
Gate Arrays : Implementation, Evaluation, and Future Projection. 2021 IEEE
International Parallel and Distributed Processing Symposium (IPDPS). https://doi.org/10.1109/ipdps49936.2021.00116'
bibtex: '@inproceedings{Karp_Podobas_Jansson_Kenter_Plessl_Schlatter_Markidis_2021,
title={High-Performance Spectral Element Methods on Field-Programmable Gate Arrays :
Implementation, Evaluation, and Future Projection}, DOI={10.1109/ipdps49936.2021.00116},
booktitle={2021 IEEE International Parallel and Distributed Processing Symposium
(IPDPS)}, publisher={IEEE}, author={Karp, Martin and Podobas, Artur and Jansson,
Niclas and Kenter, Tobias and Plessl, Christian and Schlatter, Philipp and Markidis,
Stefano}, year={2021} }'
chicago: 'Karp, Martin, Artur Podobas, Niclas Jansson, Tobias Kenter, Christian
Plessl, Philipp Schlatter, and Stefano Markidis. “High-Performance Spectral Element
Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future
Projection.” In 2021 IEEE International Parallel and Distributed Processing
Symposium (IPDPS). IEEE, 2021. https://doi.org/10.1109/ipdps49936.2021.00116.'
ieee: 'M. Karp et al., “High-Performance Spectral Element Methods on Field-Programmable
Gate Arrays : Implementation, Evaluation, and Future Projection,” 2021, doi: 10.1109/ipdps49936.2021.00116.'
mla: 'Karp, Martin, et al. “High-Performance Spectral Element Methods on Field-Programmable
Gate Arrays : Implementation, Evaluation, and Future Projection.” 2021 IEEE
International Parallel and Distributed Processing Symposium (IPDPS), IEEE,
2021, doi:10.1109/ipdps49936.2021.00116.'
short: 'M. Karp, A. Podobas, N. Jansson, T. Kenter, C. Plessl, P. Schlatter, S.
Markidis, in: 2021 IEEE International Parallel and Distributed Processing Symposium
(IPDPS), IEEE, 2021.'
date_created: 2022-02-21T14:26:37Z
date_updated: 2024-01-22T09:59:13Z
department:
- _id: '27'
- _id: '518'
doi: 10.1109/ipdps49936.2021.00116
language:
- iso: eng
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: 2021 IEEE International Parallel and Distributed Processing Symposium
(IPDPS)
publication_status: published
publisher: IEEE
quality_controlled: '1'
status: public
title: 'High-Performance Spectral Element Methods on Field-Programmable Gate Arrays
: Implementation, Evaluation, and Future Projection'
type: conference
user_id: '3145'
year: '2021'
...
---
_id: '46194'
author:
- first_name: Tobias
full_name: Kenter, Tobias
id: '3145'
last_name: Kenter
- first_name: Adesh
full_name: Shambhu, Adesh
last_name: Shambhu
- first_name: Sara
full_name: Faghih-Naini, Sara
last_name: Faghih-Naini
- first_name: Vadym
full_name: Aizinger, Vadym
last_name: Aizinger
citation:
ama: 'Kenter T, Shambhu A, Faghih-Naini S, Aizinger V. Algorithm-hardware co-design
of a discontinuous Galerkin shallow-water model for a dataflow architecture on
FPGA. In: Proceedings of the Platform for Advanced Scientific Computing Conference
(PASC). ACM; 2021. doi:10.1145/3468267.3470617'
apa: Kenter, T., Shambhu, A., Faghih-Naini, S., & Aizinger, V. (2021). Algorithm-hardware
co-design of a discontinuous Galerkin shallow-water model for a dataflow architecture
on FPGA. Proceedings of the Platform for Advanced Scientific Computing Conference
(PASC). https://doi.org/10.1145/3468267.3470617
bibtex: '@inproceedings{Kenter_Shambhu_Faghih-Naini_Aizinger_2021, title={Algorithm-hardware
co-design of a discontinuous Galerkin shallow-water model for a dataflow architecture
on FPGA}, DOI={10.1145/3468267.3470617},
booktitle={Proceedings of the Platform for Advanced Scientific Computing Conference
(PASC)}, publisher={ACM}, author={Kenter, Tobias and Shambhu, Adesh and Faghih-Naini,
Sara and Aizinger, Vadym}, year={2021} }'
chicago: Kenter, Tobias, Adesh Shambhu, Sara Faghih-Naini, and Vadym Aizinger. “Algorithm-Hardware
Co-Design of a Discontinuous Galerkin Shallow-Water Model for a Dataflow Architecture
on FPGA.” In Proceedings of the Platform for Advanced Scientific Computing
Conference (PASC). ACM, 2021. https://doi.org/10.1145/3468267.3470617.
ieee: 'T. Kenter, A. Shambhu, S. Faghih-Naini, and V. Aizinger, “Algorithm-hardware
co-design of a discontinuous Galerkin shallow-water model for a dataflow architecture
on FPGA,” 2021, doi: 10.1145/3468267.3470617.'
mla: Kenter, Tobias, et al. “Algorithm-Hardware Co-Design of a Discontinuous Galerkin
Shallow-Water Model for a Dataflow Architecture on FPGA.” Proceedings of the
Platform for Advanced Scientific Computing Conference (PASC), ACM, 2021, doi:10.1145/3468267.3470617.
short: 'T. Kenter, A. Shambhu, S. Faghih-Naini, V. Aizinger, in: Proceedings of
the Platform for Advanced Scientific Computing Conference (PASC), ACM, 2021.'
date_created: 2023-07-28T11:58:14Z
date_updated: 2024-04-17T08:12:21Z
department:
- _id: '27'
- _id: '518'
doi: 10.1145/3468267.3470617
language:
- iso: eng
main_file_link:
- url: https://dl.acm.org/doi/pdf/10.1145/3468267.3470617
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the Platform for Advanced Scientific Computing Conference
(PASC)
publication_status: published
publisher: ACM
quality_controlled: '1'
related_material:
link:
- description: Open Access available via this link.
relation: other
url: ' https://www.sighpc.org/for-our-community/acm-open-tocs/pasc21-open-toc '
status: public
title: Algorithm-hardware co-design of a discontinuous Galerkin shallow-water model
for a dataflow architecture on FPGA
type: conference
user_id: '3145'
year: '2021'
...