Skip to main content Skip to main navigation

Publikationen

Zeige Ergebnisse 1271 bis 1280 von 14470.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Dominik Hintersdorf; Lukas Struppek; Manuel Brack; Felix Friedrich; Patrick Schramowski; Kristian Kersting

    Does CLIP Know My Face?

    In: Journal of Artificial Intelligence Research (JAIR), Vol. 80, Pages 1033-1062, arXiv, 2024.

  8. Joscha Grüger

    Process Mining for Healthcare: Discover Beyond Discovery

    PhD-Thesis, Universität Trier, 2024.

  9. Jan Ehrhardt; Heinz Handels

    Implicitly Solved Regularization for Learning-Based Image Registration

    In: Xiaohuan Cao; Xuanang Xu; Islem Rekik; Zhiming Cui; Xi Ouyang (Hrsg.). Machine Learning in Medical Imaging. International Workshop on Machine Learning in Medical Imaging (MLMI-2023), located at International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), October 8, Vancouver, Canada, Pages 137-146, Lecture Notes in Computer Science (LNCS), Vol. 14348, ISBN 978-3-031-45673-2, Springer Nature Switzerland, 2024.

  10. Sascha Xu; Frank Wilhelm-Mauch; Wolfgang Maaß

    Quantum Feature Embeddings for Graph Neural Networks

    In: Hawaii International Conference on System Sciences 2024. Hawaii International Conference on System Sciences (HICSS-2024), USA, HICSS, 1/2024.

Jahr

Mehr Optionen