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Publications

Displaying results 141 to 150 of 678.

  1. Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations

    In: IEEE Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June 19-25, Pages 3619-3629, Computer Vision Foundation / IEEE, 2021.

  2. Hitesh Kotte; Milos Kravcik; Nghia Duong-Trung

    Real-Time Posture Correction in Gym Exercises: A Computer Vision-Based Approach for Performance Analysis, Error Classification and Feedback

    In: Khaleel Asyraaf Mat Sanusi; Bibeg Limbu; Jan Schneider; Milos Kravcik; Roland Klemke (Hrsg.). Proceedings of the Third International Workshop on Multimodal Immersive Learning Systems (MILeS 2023). International Workshop on Multimodal Immersive Learning Systems (MILeS-2023), located at Eighteenth European Conference on Technology Enhanced Learning (EC-TEL 2023), September 4-8, Aveiro, Portugal, Pages 64-70, Vol. 3499, CEUR Workshop Proceedings, Aachen, 10/2023.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Andrea Galassi; Kristian Kersting; Marco Lippi; Xiaoting Shao; Paolo Torroni

    Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning

    In: Frontiers in Big Data, Vol. 2 - 2019, Pages 0-10, Frontiers, 1/2020.

  9. Kristian Kersting; Miryung Kim; Guy Van den Broeck; Thomas Zimmermann

    SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091)

    In: Dagstuhl Reports, Vol. 10, No. 2, Pages 76-87, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2020.

  10. Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

    In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Conference on Artificial Intelligence (AAAI-2021), Pages 9533-9540, AAAI Press, 2021.

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