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Publications

Displaying results 131 to 140 of 682.

  1. 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.

  2. 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.

  3. 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.

  4. David Steinmann; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting

    Machines Explaining Linear Programs

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2206.07194, Pages 0-10, arXiv, 2022.

  5. Xiaoting Shao; Kristian Kersting

    Gradient-based Counterfactual Explanations using Tractable Probabilistic Models

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2205.07774, Pages 0-10, arXiv, 2022.

  6. Daniel Hernández-Lobato; Viktoriia Sharmanska; Kristian Kersting; Christoph H. Lampert; Novi Quadrianto

    Mind the Nuisance: Gaussian Process Classification using Privileged Noise

    In: Zoubin Ghahramani; Max Welling; Corinna Cortes; Neil D. Lawrence; Kilian Q. Weinberger (Hrsg.). Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014. Neural Information Processing Systems (NeurIPS-2014), December 8-13, Montreal, Quebec, Canada, Pages 837-845, Curran Associates, Inc. 2014.

  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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