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Publications

Displaying results 281 to 290 of 682.

  1. 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.

  2. Zihan Ye; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Differentiable Meta logical Programming

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.11650, Pages 0-10, arXiv, 2022.

  3. Quentin Delfosse; Wolfgang Stammer; Thomas Rothenbacher; Dwarak Vittal; Kristian Kersting

    Boosting Object Representation Learning via Motion and Object Continuity

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2211.09771, Pages 0-10, arXiv, 2022.

  4. Dominik Hintersdorf; Lukas Struppek; Kristian Kersting

    CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2209.07341, Pages 0-10, arXiv, 2022.

  5. Frieder Uhlig; Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

    Transformer-Boosted Anomaly Detection with Fuzzy Hashes

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2208.11367, Pages 0-10, arXiv, 2022.

  6. Jonas Seng; Pooja Prasad; Devendra Singh Dhami; Kristian Kersting

    HANF: Hyperparameter And Neural Architecture Search in Federated Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2206.12342, Pages 0-10, arXiv, 2022.

  7. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  8. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

  9. Claas Völcker; Alejandro Molina; Johannes Neumann; Dirk Westermann; Kristian Kersting

    DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets

    In: Peggy Cellier; Kurt Driessens (Hrsg.). Machine Learning and Knowledge Discovery in Databases. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2019), International Workshops of ECML PKDD 2019, Proceedings, Part I, September 16-20, Würzburg, Germany, Pages 28-43, Communications in Computer and Information Science, Vol. 1167, Springer, 2019.

  10. Navdeep Kaur; Gautam Kunapuli; Saket Joshi; Kristian Kersting; Sriraam Natarajan

    Neural Networks for Relational Data

    In: Dimitar Kazakov; Can Erten (Hrsg.). Inductive Logic Programming - 29th International Conference, Proceedings. International Conference on Inductive Logic Programming (ILP-2019), September 3-5, Plovdiv, Bulgaria, Pages 62-71, Lecture Notes in Computer Science (LNAI), Vol. 11770, Springer, 2019.

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