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Publications

Displaying results 41 to 50 of 14521.

  1. Lukas Struppek; Minh Hieu Le; Dominik Hintersdorf; Kristian Kersting

    Exploring the Adversarial Capabilities of Large Language Models

    2024.

  2. Saurabh Mathur; Veerendra P. Gadekar; Rashika Ramola; Peixin Wang; Ramachandran Thiruvengadam; David M. Haas; Shinjini Bhatnagar; Nitya Wadhwa; Garbhini Study Group; Predrag Radivojac; Himanshu Sinha; Kristian Kersting; Sriraam Natarajan

    Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources

    In: Joseph Finkelstein; Robert Moskovitch; Enea Parimbelli (Hrsg.). Artificial Intelligence in Medicine - 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part I. Conference on Artificial Intelligence in Medicine (AIME), Pages 293-302, Lecture Notes in Computer Science, Vol. 14844, Springer, 2024.

  3. Jonas Seng; Florian Peter Busch; Kristian Kersting

    Causality in Flux: Continual Adaptation of Causal Knowledge via Evidence Matching

    In: Martin Mundt; Keiland W. Cooper; Devendra Singh Dhami; Tyler L. Hayes; Rebecca Herman; Adéle Ribeiro; James Seale Smith (Hrsg.). Proceedings of The Second AAAI Bridge Program on Continual Causality. AAAI Bridge Program on Continual Causality, February 20-21, Vancouver, Canada, Pages 11-20, Proceedings of Machine Learning Research (PMLR), Vol. 268, PMLR, 2024.

  4. Wolfgang Stammer; Felix Friedrich; David Steinmann; Manuel Brack; Hikaru Shindo; Kristian Kersting

    Learning by Self-Explaining

    In: Transactions on Machine Learning Research (TMLR), Vol. 2024, Pages 1-35, arXiv, 2024.

  5. Daniel Ochs; Karsten Wiertz; Sebastian Bußmann; Kristian Kersting; Devendra Singh Dhami

    Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images

    In: Remote Sensing, Vol. 16, No. 2, Pages 1-13, MDPI, 2024.

  6. Hikaru Shindo; Viktor Pfanschilling; Devendra Singh Dhami; Kristian Kersting

    Learning differentiable logic programs for abstract visual reasoning

    In: Journal of Machine Learning Research (JMLR), Vol. 113, No. 11, Pages 8533-8584, arXiv, 2024.

  7. Matej Zecevic; Devendra Singh Dhami; Kristian Kersting

    Structural causal models reveal confounder bias in linear program modelling

    In: Journal of Machine Learning Research (JMLR), Vol. 113, No. 3, Pages 1329-1349, Springer, 2024.

  8. Gerrit Großmann; Larisa Ivanova; Sai Leela Poduru; Mohaddeseh Tabrizian; Islam Mesabah; David Antony Selby; Sebastian Vollmer

    The Power of Stories: Narrative Priming in Multi-Agent Networked Public Goods Games

    In: Proceedings of the 12th INternational Conference of Networks, Games, Control and Optimization. International Conference of Networks, Games, Control and Optimization (NETGCOOP-2025), October 8-10, Bilbao, Spain, Lecture Notes in Computer Science (LNCS), Springer, 10/2025.

  9. David Antony Selby; Rashika Jakhmola; Maximilian Sprang; Gerrit Großmann; Hind Raki; Niloofar Maani; Daria Pavliuk; Jan Ewald; Sebastian Vollmer

    Visible neural networks for multi-omics integration: a critical review

    In: Frontiers in Artificial Intelligence, Vol. 8, Pages 1-1, Frontiers Media S.A. 2025.

  10. David Antony Selby; Yuichiro Iwashita; Kai Spriestersbach; Mohammad Saad; Dennis Bappert; Archana Warrier; Sumantrak Mukherjee; Koichi Kise; Sebastian Vollmer

    Had enough of experts? Quantitative knowledge retrieval from large language models

    In: Weijie Su; Linjun Zhang; David Banks (Hrsg.). The ISI's Journal for the Rapid Dissemination of Statistics Research (Stat), Vol. 14, Pages e70054-n.n. Wiley, 3/2025.

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