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Publikationen

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  1. Manuel Brack; Felix Friedrich; Katharina Kornmeier; Linoy Tsaban; Patrick Schramowski; Kristian Kersting; Apolinaros Passos

    LEDITS++: Limitless Image Editing using Text-to-Image Models

    In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). International Conference on Computer Vision and Pattern Recognition (CVPR-2024), 2024.

  2. Quentin Delfosse; Patrick Schramowski; Martin Mundt; Alejandro Molina; Kristian Kersting

    Adaptive Rational Activations to Boost Deep Reinforcement Learning

    In: Proceedings of the International Conference on Representation Learning (ICLR). International Conference on Learning Representations (ICLR-2024), OpenReview.net, 2024.

  3. Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks

    In: International Conference on Learning Representations (ICLR). International Conference on Learning Representations (ICLR-2024), OpenReview, 2024.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.