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777 Publications
2022 | Journal Article | LibreCat-ID: 30591
R. Bertling, M. Hack, I. Ausner, B. Horschitz, S. A. Bernemann, and E. Kenig, “Modelling film and rivulet flows on microstructured surfaces using CFD methods,” Chemical Engineering Science, vol. 251, Art. no. 117414, 2022, doi: 10.1016/j.ces.2021.117414.
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2022 | Conference Paper | LibreCat-ID: 33739 | 
A. Bondarenko et al., “CausalQA: A Benchmark for Causal Question Answering,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 3296–3308.
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2022 | Conference Paper | LibreCat-ID: 46193 |
M. Karp et al., “A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays: Design, Evaluation, and Future Challenges,” 2022, doi: 10.1145/3492805.3492808.
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2022 | Preprint | LibreCat-ID: 32404
T. Kühne, C. Plessl, R. Schade, and O. Schütt, “CP2K on the road to exascale,” arXiv:2205.14741. 2022.
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| arXiv
2022 | Journal Article | LibreCat-ID: 33226 |
R. Schade, C. Bauer, K. Tamoev, L. Mazur, C. Plessl, and T. Kühne, “Parallel quantum chemistry on noisy intermediate-scale quantum computers,” Phys. Rev. Research, vol. 4, p. 033160, 2022, doi: 10.1103/PhysRevResearch.4.033160.
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2022 | Journal Article | LibreCat-ID: 33684 |
R. Schade et al., “Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms,” Parallel Computing, vol. 111, Art. no. 102920, 2022, doi: 10.1016/j.parco.2022.102920.
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2022 | Journal Article | LibreCat-ID: 27364
M. Meyer, T. Kenter, and C. Plessl, “In-depth FPGA Accelerator Performance Evaluation with Single Node Benchmarks from the HPC Challenge Benchmark Suite for Intel and Xilinx FPGAs using OpenCL,” Journal of Parallel and Distributed Computing, 2022, doi: 10.1016/j.jpdc.2021.10.007.
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| DOI
2022 | Report | LibreCat-ID: 49113
J. Ebbers and R. Haeb-Umbach, Pre-Training And Self-Training For Sound Event Detection In Domestic Environments. 2022.
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2022 | Conference Paper | LibreCat-ID: 33509
C. Marschalt et al., “Far-field Calculation from magnetic Huygens Box Data using the Boundary Element Method,” presented at the 2022 Smart Systems Integration (SSI), Grenoble, France, 2022, doi: 10.1109/ssi56489.2022.9901431.
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2022 | Conference Paper | LibreCat-ID: 33848 |
T. Cord-Landwehr, C. Boeddeker, T. von Neumann, C. Zorila, R. Doddipatla, and R. Haeb-Umbach, “Monaural source separation: From anechoic to reverberant environments,” presented at the 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 2022.
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| arXiv
2022 | Conference Paper | LibreCat-ID: 33819 |
T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “SA-SDR: A Novel Loss Function for Separation of Meeting Style Data,” 2022, doi: 10.1109/icassp43922.2022.9746757.
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2022 | Misc | LibreCat-ID: 33816 |
T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer, and R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network. arXiv, 2022.
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2022 | Conference Paper | LibreCat-ID: 33954 |
C. Boeddeker, T. Cord-Landwehr, T. von Neumann, and R. Haeb-Umbach, “An Initialization Scheme for Meeting Separation with Spatial Mixture Models,” 2022, doi: 10.21437/interspeech.2022-10929.
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2021 | Conference Paper | LibreCat-ID: 27365
M. Meyer, “Towards Performance Characterization of FPGAs in Context of HPC using OpenCL Benchmarks,” 2021, doi: 10.1145/3468044.3468058.
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2021 | Journal Article | LibreCat-ID: 21004
M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label Classification: Overview and Empirical Evaluation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1–1, 2021, doi: 10.1109/tpami.2021.3051276.
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2021 | Journal Article | LibreCat-ID: 21065 |
R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, and T. Nakatani, “Far-Field Automatic Speech Recognition,” Proceedings of the IEEE, vol. 109, no. 2, pp. 124–148, 2021.
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2021 | Journal Article | LibreCat-ID: 21092
F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence.
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