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Publications

Displaying results 281 to 290 of 682.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Neuro-Symbolic Forward Reasoning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2110.09383, Pages 0-10, arXiv, 2021.

  7. Zhongjie Yu; Fabrizio Ventola; Kristian Kersting

    Whittle Networks: A Deep Likelihood Model for Time Series

    In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2021), July 18-24, Pages 12177-12186, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

  8. Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations

    In: IEEE Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June 19-25, Pages 3619-3629, Computer Vision Foundation / IEEE, 2021.

  9. Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

    In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Conference on Artificial Intelligence (AAAI-2021), Pages 9533-9540, AAAI Press, 2021.

  10. Zihan Ye; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Differentiable Meta logical Programming

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.11650, Pages 0-10, arXiv, 2022.

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