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Publications

Displaying results 281 to 290 of 661.

  1. . (Hrsg.)

    DeiSAM: Segment Anything with Deictic Prompting

    AAAI Workshop on Neuro-Symbolic Learning and Reasoning in the Era of Large Language Models, located at AAAI, 2024.

  2. Johannes Rust; Christian Mandel; Kathrin Stich; Serge Autexier

    Predicting Hemodynamic and Pulmonary Decompensation with Deep Neural Networks: Performance and Explainability

    In: 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC-2024), Orlando, USA, 2024.

  3. Sk Aziz Ali; Mohammad Sadil Khan; Didier Stricker

    BRep Boundary and Junction Detection for CAD Reverse Engineering

    In: Proceedings of the 3rd IEEE International Conference on Computing and Machine Intelligence. IEEE International Conference on Computing and Machine Intelligence (ICMI-2024), April 13-14, Michigan, MI, USA, IEEE, 2024.

  4. Hikaru Shindo; Viktor Pfanschilling; Devendra Singh Dhami; Kristian Kersting

    (alpha)ILP: thinking visual scenes as differentiable logic programs

    In: Machine Learning, Vol. 112, No. 5, Pages 1465-1497, Springer, 2023.

  5. Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters

    Sharing Knowledge in Multi-Task Deep Reinforcement Learning

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

  6. 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.

  7. 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.

  8. 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.

  9. Riad Akrour; Davide Tateo; Jan Peters

    Reinforcement Learning from a Mixture of Interpretable Experts

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2006.05911, Pages 0-10, arXiv, 2020.

  10. Andrea Cini; Carlo D'Eramo; Jan Peters; Cesare Alippi

    Deep Reinforcement Learning with Weighted Q-Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2003.09280, Pages 0-10, arXiv, 2020.

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