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Publications

Displaying results 271 to 280 of 579.

  1. 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.

  2. Daniel Tanneberg; Alexandros Paraschos; Jan Peters; Elmar Rueckert

    Deep spiking networks for model-based planning in humanoids

    In: 16th IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2016), November 15-17, Cancun, Mexico, Pages 656-661, IEEE, 2016.

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

    Value Iteration in Continuous Actions, States and Time

    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 7224-7234, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

  4. 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.

  5. Riad Akrour; Asma Atamna; Jan Peters

    Convex optimization with an interpolation-based projection and its application to deep learning

    In: Machine Learning, Vol. 110, No. 8, Pages 2267-2289, Springer, 2021.

  6. Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters; Marcello Restelli

    Gaussian Approximation for Bias Reduction in Q-Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 277:1-277:51, JMLR, 2021.

  7. Niyati Rawal; Dorothea Koert; Cigdem Turan; Kristian Kersting; Jan Peters; Ruth Stock-Homburg

    ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition

    In: Frontiers in Robotics and AI, Vol. 8, Pages 0-10, Frontiers, 2021.

  8. Michael Backenköhler; Paula Linh Kramer; Joschka Groß; Gerrit Großmann; Roman Joeres; Azat Tagirdzhanov; Dominique Sydow; Hamza Ibrahim; Floriane Odje; Verena Wolf; Andrea Volkamer

    TeachOpenCADD goes Deep Learning: Open-source Teaching Platform Exploring Molecular DL Applications

    In: ChemRxiv, Vol. ChemRxiv Online, ChemRxiv.org, 5/2023.

  9. Burak Mergen; Tarek Safi; Matthias Nadig; Gopal Bhattrai; Loay Daas; Jan Alexandersson; Berthold Seitz

    Detecting the corneal neovascularisation area using artificial intelligence

    In: British Journal of Ophthalmology (BJO), BMJ Publishing Group Ltd, 2023.

  10. Dinh Nam Pham; Vera Czehmann; Eleftherios Avramidis

    Disambiguating Signs: Deep Learning-based Gloss-level Classification for German Sign Language by Utilizing Mouth Actions

    In: Proceedings of the 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN-2023), October 4-6, Bruges, Belgium, ISBN 978-2-87587-088-9. i6doc.com publ. 10/2023.

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