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Publikationen

Zeige Ergebnisse 1431 bis 1440 von 14740.

  1. Faeze Faghih; Tobias Ziegler; Zsolt István; Carsten Binnig

    SmartNICs in the Cloud: The Why, What and How of In-network Processing for Data-Intensive Applications

    In: Pablo Barceló; Nayat Sánchez-Pi; Alexandra Meliou; S. Sudarshan (Hrsg.). Companion of the 2024 International Conference on Management of Data, SIGMOD/PODS 2024, Santiago, Chile, June 9-15, 2024. ACM SIGMOD International Conference on Management of Data (SIGMOD), Pages 556-560, ACM, 2024.

  2. Faeze Faghih; Tobias Ziegler; Zsolt István; Carsten Binnig

    SmartNICs in the Cloud: The Why, What and How of In-network Processing for Data-Intensive Applications

    In: Pablo Barceló; Nayat Sánchez-Pi; Alexandra Meliou; S. Sudarshan (Hrsg.). Companion of the 2024 International Conference on Management of Data, SIGMOD/PODS 2024, Santiago, Chile, June 9-15, 2024. ACM SIGMOD International Conference on Management of Data (SIGMOD), Pages 556-560, ACM, 2024.

  3. Nadja Geisler; Carsten Binnig

    Towards Extending XAI for Full Data Science Pipelines

    In: Jean-Daniel Fekete; Behrooz Omidvar-Tehrani; Kexin Rong; Roee Shraga (Hrsg.). Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics, HILDA 24, Santiago, Chile, 14 June 2024. Workshop on Human-In-the-Loop Data Analytics (HILDA), Pages 1-7, ACM, 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.

  10. 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.

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