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Publikationen

 

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  1. Zhongjie Yu; Fabrizio Ventola; Kristian Kersting

    Whittle Networks: A Deep Likelihood Model for Time Series

    In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine …

  2. Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations

    In: IEEE Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June …

  3. Moritz Willig; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting

    The Causal Loss: Driving Correlation to Imply Causation

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2110.12066, Pages 0-10, arXiv, 2021.

  4. Matej Zecevic; Devendra Singh Dhami; Kristian Kersting

    On the Tractability of Neural Causal Inference

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2110.12052, Pages 0-10, arXiv, 2021.

  5. Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

    In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Conference on Artificial Intelligence (AAAI-2021), Pages 9533-9540, AAAI …

  6. Sophie Burkhardt; Jannis Brugger; Nicolas Wagner; Zahra Ahmadi; Kristian Kersting; Stefan Kramer

    Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation

    In: Frontiers in Artificial Intelligence, Vol. 4, Pages 0-10, Frontiers, 2021.

  7. Plinio Moreno; Alexandre Bernardino; José Santos-Victor; Rodrigo M. M. Ventura; Kristian Kersting

    Editorial: Robots that Learn and Reason: Towards Learning Logic Rules from Noisy Data

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

  8. Nandini Ramanan; Gautam Kunapuli; Tushar Khot; Bahare Fatemi; Seyed Mehran Kazemi; David Poole; Kristian Kersting; Sriraam Natarajan

    Structure learning for relational logistic regression: an ensemble approach

    In: Data Mining and Knowledge Discovery, Vol. 35, No. 5, Pages 2089-2111, Springer, 2021.

  9. Silke Balzert-Walter; Freek Bomhof; Barteld Braaksma; Giuseppe Ciulla; Roberto Di Bernardo; Giovanna Galasso; Matteo Gerosa; Alexa Kodde

    Report on the key findings from the Theme Development Workshop “AI in the Public Sector”

    Pages 1-18, 11/2021.

  10. Pascal Klink; Hany Abdulsamad; Boris Belousov; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 182:1-182:52, JMLR, 2021.