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Publications

Displaying results 301 to 310 of 681.

  1. 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.

  2. 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.

  3. 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.

  4. Sebastián Gómez-González; Sergey Prokudin; Bernhard Schölkopf; Jan Peters

    Real Time Trajectory Prediction Using Deep Conditional Generative Models

    In: IEEE Robotics and Automation Letters (RA-L), Vol. 5, No. 2, Pages 970-976, IEEE, 2020.

  5. Julien Brosseit; Benedikt Hahner; Fabio Muratore; Michael Gienger; Jan Peters

    Distilled Domain Randomization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2112.03149, Pages 0-10, arXiv, 2021.

  6. Antoine Grosnit; Rasul Tutunov; Alexandre Max Maraval; Ryan-Rhys Griffiths; Alexander I. Cowen-Rivers; Lin Yang; Lin Zhu; Wenlong Lyu; Zhitang Chen; Jun Wang; Jan Peters; Haitham Bou-Ammar

    High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2106.03609, Pages 0-10, arXiv, 2021.

  7. Michael Lutter; Shie Mannor; Jan Peters; Dieter Fox; Animesh Garg

    Robust Value Iteration for Continuous Control Tasks

    In: Dylan A. Shell; Marc Toussaint; M. Ani Hsieh (Hrsg.). Robotics: Science and Systems XVII. Robotics: Science and Systems (RSS-2021), July 12-16, Virtual Event, Robotics Science and Systems, Online Proceedings, 2021.

  8. Jayasankar Santhosh; David Dzsotjan; Shoya Ishimaru

    Multimodal Assessment of Interest Levels in Reading: Integrating Eye-Tracking and Physiological Sensing

    In: IEEE Access (IEEE), Vol. 11, Pages 93994-94008, IEEE, 9/2023.

  9. Andrew S. Morgan; Daljeet Nandha; Georgia Chalvatzaki; Carlo D'Eramo; Aaron M. Dollar; Jan Peters

    Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning

    In: IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation (ICRA-2021), May 30 - June 5, Xi'an, China, Pages 6672-6678, IEEE, 2021.

  10. Vincent Vandeghinste; Mirella De Sisto; Maria Kopf; Davy Van Landuyt Picron; Irene Murtagh; Eleftherios Avramidis; Mathieu De Coster

    European Language Equality, Report on Europe's Sign Languages

    In: Maria Giagkou; Stelios Piperidis; Georg Rehm; Jane Dunne (Hrsg.). Project European Language Equality (ELE). Pages 1-31, ELE Consortium, 5/2023.

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