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Publications

Displaying results 1321 to 1330 of 15056.

  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 Learning (ICML-2021), July 18-24, Pages 12177-12186, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

  2. Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    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 19-25, Pages 3619-3629, Computer Vision Foundation / IEEE, 2021.

  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 Press, 2021.

  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 1-10, Frontiers, 2021.

  7. Marion Neumann; Roman Garnett; Christian Bauckhage; Kristian Kersting

    Propagation kernels: efficient graph kernels from propagated information

    In: Machine Learning, Vol. 102, No. 2, Pages 209-245, Springer, 2016.

  8. Piotr Szymanski; Tomasz Kajdanowicz; Kristian Kersting

    How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?

    In: Entropy, Vol. 18, No. 8, Pages 0-10, MDPI, 2016.

  9. Mahdi Chamseddine; Kaufmann Fabian; Schellen Marius; Glock Christian; Didier Stricker; Jason Raphael Rambach

    BIMStruct3D: A Fully Automated Hybrid Learning Scan-to-BIM Pipeline with Integrated Topology Refinement

    In: Computing in Construction. European Conference on Computing in Construction (EC3-2026), 2026 European Conference on Computing in Construction, July 12-15, Corfu, Greece, ISBN 978-90-834513-2-9, EC3, 2026.

  10. Jonas Eisenmenger; Zhongqian Zhao; Pierre Willenbrock; Wiebke Brinkmann

    DFKI-X2D: Design and Testing of a Quasi-Direct Drive Motor for Space Applications

    In: 15th EASN International Conference on Innovation in Aviation & Space Towards Sustainability Today & Tomorrow. EASN International Conference on Innovation in Aviation & Space towards Sustainability Today & Tomorrow (EASN-2025), October 14-17, Madrid, Spain, MDPI, Engineering Proceedings, volume 133, 4/2026.

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