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Publications

Displaying results 141 to 150 of 681.

  1. Arnab Das; Carlos Franzreb; Tim Polzehl; Sebastian Möller

    Exploring Foundation Model Fusion Effectiveness and Explainability for Stylistic Analysis of Emotional Podcast Data

    In: Advances in Information and Communication. Future of Information and Communication Conference (FICC-2025), located at FICC-2025, March 4-5, Berlin, Germany, Springer Nature, Switzerland, 2025.

  2. Elnaz Azmi; Khadijeh Alibabaei; Valentin Kozlov; Tjerk Krijger; Gabriele Accarino; Igor Ruiz Atake; Sakina-Dorothée Ayata; Amanda Calatrava; Marco Mariano De Carlo; Wout Decrop; Donatello Elia; Sandro Luigi Fiore; Marco Francescangeli; Jesús Soriano-González; Jean-Olivier Irisson; Martin Laviale; Rune Lagaisse; Antoine Lebeaud; Carolin Leluschko; Germán Moltó; Antonio Augusto Sepp Neves; Enoc Martinez; Damian Smyth; Muhammad Arabi Tayyab; Vanessa Tosello; Alvaro Lopez Garcia; Dick Schaap; Gergely Sipos

    Best practices for AI-based image analysis applications in aquatic sciences: The iMagine case study

    In: Ecological Informatics, Vol. 91, Pages 1-37, Elsevier, Amsterdam, 7/2025.

  3. Dinh Nam Pham; Eleftherios Avramidis

    The Importance of Facial Features in Vision-based Sign Language Recognition: Eyes, Mouth or Full Face?

    In: ACM International Conference on Intelligent Virtual Agents (IVA Adjunct ’25). International Workshop on Sign Language Translation and Avatar Technology (SLTAT-2025), 9th International Workshop on Sign Language Translation and Avatar Technology, located at IVA-2025, September 16, Berlin, Germany, ISBN 979-8-4007-1996-7/25/09, ACM, 9/2025.

  4. Ankur Bhatt; Ko Watanabe; Jayasankar Santhosh; Andreas Dengel; Shoya Ishimaru

    ABCDE: Appearance-Based Confidence Detection by Evaluating Gaze Behavior Using Deep Learning

    In: International Journal of Activity and Behavior Computing, Vol. 2025 1, Pages 1-24, Care XDX Center, Kyushu Institute of Technology, 7/2025.

  5. Tim Dahmen; Niklas Rottmayer; Katja Schladitz; Markus Kronenberger; Ziwei He; Miriam Hommel; Petra Gospodnetic; Claudia Redenbach

    Combining Stochastic Geometry and Neural Models of Electron Matter Interaction for the Simulation of Electron Imaging of Porous Materials

    In: Proceedings of the XI International Conference on Coupled Problems in Science and Engineering. International Conference on Coupled Problems in Science and Engineering (Coupled Problems-2025), May 25-28, Villasimius, Sardinia, Italy, IACM, 2025.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Karl Stelzner; Robert Peharz; Kristian Kersting

    Faster Attend-Infer-Repeat with Tractable Probabilistic Models

    In: Kamalika Chaudhuri; Ruslan Salakhutdinov (Hrsg.). Proceedings of the 36th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2019), June 9-15, Long Beach, California, USA, Pages 5966-5975, Proceedings of Machine Learning Research, Vol. 97, PMLR, 2019.

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