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Publications

Displaying results 141 to 150 of 678.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Alejandro Molina; Sriraam Natarajan; Kristian Kersting

    Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions

    In: Satinder Singh; Shaul Markovitch (Hrsg.). Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-2017), February 4-9, San Francisco, California, USA, Pages 2357-2363, AAAI Press, 2017.

  7. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Kristian Kersting; Zoubin Ghahramani

    Probabilistic Deep Learning using Random Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1806.01910, Pages 0-10, arXiv, 2018.

  8. Lukas Sommer; Julian Oppermann; Alejandro Molina; Carsten Binnig; Kristian Kersting; Andreas Koch

    Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators

    In: 36th IEEE International Conference on Computer Design. IEEE International Conference on Computer Design (ICCD-2018), October 7-10, Orlando, FL, USA, Pages 350-357, IEEE Computer Society, 2018.

  9. Antonio Vergari; Robert Peharz; Nicola Di Mauro; Alejandro Molina; Kristian Kersting; Floriana Esposito

    Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks

    In: Sheila A. McIlraith; Kilian Q. Weinberger (Hrsg.). Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-18), Pages 4163-4170, AAAI Press, 2018.

  10. Alejandro Molina; Antonio Vergari; Nicola Di Mauro; Sriraam Natarajan; Floriana Esposito; Kristian Kersting

    Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains

    In: Sheila A. McIlraith; Kilian Q. Weinberger (Hrsg.). Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-18), Pages 3828-3835, AAAI Press, 2018.

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