The Concept of a Digital Twin and Its Potential for Learning Organizations
Angelina Berisha-Gawlowski, C. Caruso, C. Harteis, in: D. Ifenthaler, S. Hofhues, M. Egloffstein, C. Helbig (Eds.), Digital Transformation of Learning Organizations  , Springer, Cham, 2021, pp. 95–114.

Conventional and Machine Learning Approaches for Network and Service Coordination
S.B. Schneider, Conventional and Machine Learning Approaches for Network and Service Coordination, 2021.

Cost of Debt for Private Firms Revisited: Voluntary Audits as a Reflection of Risk
R. Ichev, J. Koren, U. Kosi, K. Sitar Sustar, A. Valentincic, Cost of Debt for Private Firms Revisited: Voluntary Audits as a Reflection of Risk, 2021.

PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data
O. Müller, M. Caron, M. Döring, T. Heuwinkel, J. Baumeister, in: 8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021), n.d.

Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening
B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, in: G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, Y. Yoshida (Eds.), Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &; Materials Series., Springer, Cham, 2021, pp. 1495–1506.

Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel
B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, in: 2021.

Conceptualising and measuring domain-specific content knowledge of early childhood educators: A systematic review
J. Bruns, H. Gasteiger, C. Strahl, Review of Education 9 (2021) 500–538.

Self-Driving Network and Service Coordination Using Deep Reinforcement Learning
S.B. Schneider, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, R. Khalili, A. Hecker, in: IEEE International Conference on Network and Service Management (CNSM), IEEE, 2020.

Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel
C.-M. Kuball, B. Uhe, G. Meschut, M. Merklein, eds., Process Design for the Forming of Semi-Tubular Self-Piercing Rivets Made of High Nitrogen Steel, 2020.

SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH
J. Kersting, F.S. Bäumer, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.

Aspect Phrase Extraction in Sentiment Analysis with Deep Learning
J. Kersting, M. Geierhos, in: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, Setúbal, Portugal, 2020, pp. 391--400.

Stress state dependent damage modeling of self-pierce riveting process simulation using GISSMO damage model
M. Otroshi, M. Rossel, G. Meschut, Journal of Advanced Joining Processes 1 (2020).

Conceptual Change in the Face of Digitalization
C. Harteis, M. Goller, C. Caruso, Frontiers in Education 5 (2020).

Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen
C. Caruso, C. Adammek, S. Bonanati, S. Wiescholek, Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion 3 (2020) 18–33.

Influence of the process temperature on the forming behaviour and the friction during bulk forming of high nitrogen steel
C.-M. Kuball, R. Jung, B. Uhe, G. Meschut, M. Merklein, eds., Influence of the Process Temperature on the Forming Behaviour and the Friction during Bulk Forming of High Nitrogen Steel, 2020.

Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints
B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, Production Engineering 14 (2020) 417–423.

Informationskompetenz durch E-Learning? Durch Lernvideos nach Literatur suchen
C.A. Hahn, die hochschullehre (2020).

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: Parallel Problem Solving from Nature (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 48–64.

Squaring the circle: Business model teaching in large classroom settings
D. Szopinski, Journal of Business Models 7 (2019) 90–100.

A Hypothetical Learning Trajectory for the Learning of the Rules for Manipulating Integers
J. Schumacher, S. Rezat, in: U.T. Jankvist, M. Van den Heuvel-Panhuizen, M. Veldhuis (Eds.), Proceedings of the Eleventh Congress of the European Society for Research in Mathematics Education (CERM, February 6 – 10, 2019), Freudenthal Group &; Freudenthal Institute, Utrecht University and ERME, Utrecht, the Netherlands, n.d.