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Publications

Displaying results 141 to 150 of 571.

  1. Kristian Kersting; Miryung Kim; Guy Van den Broeck; Thomas Zimmermann

    SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091)

    In: Dagstuhl Reports, Vol. 10, No. 2, Pages 76-87, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2020.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal

    Exploiting Concepts of Instance Segmentation to Boost Detection in Challenging Environments

    In: Sensors - Open Access Journal (Sensors), Vol. 22, Pages 3703-3722, MDPI, Switzerland, 5/2022.

  8. Sungho Suh; Vitor Fortes Rey; Paul Lukowicz

    Adversarial Deep Feature Extraction Network for User Independent Human Activity Recognition

    In: 2022 IEEE International Conference on Pervasive Computing and Communications (PerCom). IEEE International Conference on Pervasive Computing and Communications (PerCom-2022), March 21-25, Pisa, Italy, Pages 217-226, IEEE, 2022.

  9. Isaak Mitschke; Thomas Wiemann; Felix Igelbrink; Joachim Hertzberg

    Hyperspectral 3D Point Cloud Segmentation using RandLA-Net

    In: Proceedings of 17th INTERNATIONAL CONFERENCE ON INTELLIGENT AUTONOMOUS SYSTEMS (IAS-17). International Conference on Intelligent Autonomous Systems (IAS-2022), June 13-16, Zagreb, Croatia, IAS, 6/2022.

  10. Michael Barz; Daniel Sonntag

    Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze

    In: Sensors - Open Access Journal (Sensors), Vol. 21, No. 12, Page 21, MDPI, 2021.

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