Publications

Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting

Neural-Probabilistic Answer Set Programming

In: Gabriele Kern-Isberner; Gerhard Lakemeyer; Thomas Meyer (Hrsg.). Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning. International Conference on Principles of Knowledge Representation and Reasoning (KR-2022), July 31 - August 5, Haifa, Israel, IJCAI Organization, 2022.

Nandini Ramanan; Mayukh Das; Kristian Kersting; Sriraam Natarajan

Discriminative Non-Parametric Learning of Arithmetic Circuits

In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 353-364, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT-22), June 21-24, Seoul, Korea, Republic of, Pages 58-69, ISBN 978-1-4503-9352-2, ACM, 2022.

Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting

Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2001.05371, Pages 0-10, arXiv, 2020.

Xiaoting Shao; Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting

Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures

In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 401-412, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

Robert Peharz; Steven Lang; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Guy Van den Broeck; Kristian Kersting; Zoubin Ghahramani

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

In: Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2020), July 13-18, Pages 7563-7574, Proceedings of Machine Learning Research, Vol. 119, PMLR, 2020.

Alejandro Molina; Patrick Schramowski; Kristian Kersting

Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks

In: 8th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2020), April 26-30, Addis Ababa, Ethiopia, OpenReview.net, 2020.

Amos Treiber; Alejandro Molina; Christian Weinert; Thomas Schneider; Kristian Kersting

CryptoSPN: Expanding PPML beyond Neural Networks

In: Benyu Zhang; Raluca Ada Popa; Matei Zaharia; Guofei Gu; Shouling Ji (Hrsg.). PPMLP'20: Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice. Workshop on Privacy-Preserving Machine Learning in Practice (PPMLP-20), located at CS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, November 9, Virtual Event, Pages 9-14, ISBN 978-1-4503-8088-1, ACM, 2020.

Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Franziska Herbert; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting

Making deep neural networks right for the right scientific reasons by interacting with their explanations

In: Nature Machine Intelligence, Vol. 2, No. 8, Pages 476-486, Springer, 2020.

Johannes Czech; Moritz Willig; Alena Beyer; Kristian Kersting; Johannes Fürnkranz

Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data

In: Frontiers in Artificial Intelligence, Vol. 3, Pages 1-10, Frontiers, 2020.