Publications

Nandini Ramanan; Mayukh Das; Kristian Kersting; Sriraam Natarajan

Discriminative Non-Parametric Learning of Arithmetic Circuits

In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 353-364, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT-22), June 21-24, Seoul, Korea, Republic of, Pages 58-69, ISBN 978-1-4503-9352-2, ACM, 2022.

Zhongjie Yu; Fabrizio Ventola; Kristian Kersting

Whittle Networks: A Deep Likelihood Model for Time Series

In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2021), July 18-24, Pages 12177-12186, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

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.

Théo Vincent; Tim Lukas Faust; Yogesh Tripathi; Jan Peters; Carlo D'Eramo

Eau De Q-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

In: Proceedings of the 2nd Reinforcement Learning Conference 2025. Reinforcement Learning Conference (RLC-2025), August 5-9, Edmonton, AB, Canada, Reinforcement Learning Journal (RLJ), 2025.

Snehal Walunj; Nazanin Mashhaditafreshi; Parsha Pahlevannejad; Achim Wagner; Martin Ruskowski

Human-Robot Interaction Through Egocentric Hand Gesture Recognition

In: Kosmas Alexopoulos; Sotiris Makris; Panagiotis Stavropoulos (Hrsg.). Advances in Artificial Intelligence in Manufacturing II. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2024), Cham, Pages 125-133, ISBN 978-3-031-86489-6, Springer Nature Switzerland, 2025.

Vinit Vikas Hegiste; Tatjana Legler; Martin Ruskowski

Collaborative Learning in Shared Production Environment Using Federated Image Classification

In: Kosmas Alexopoulos; Sotiris Makris; Panagiotis Stavropoulos (Hrsg.). Advances in Artificial Intelligence in Manufacturing II. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2024), Cham, Pages 98-106, ISBN 978-3-031-86489-6, Springer Nature Switzerland, 2025.

Christoph Peter Balada; Aida Romano-Martinez; Vincent ten Cate; Katharina Geschke; Jonas Tesarz; Paul Claßen; Alexander K Schuster; Dativa Tibyampansha; Karl-Patrik Kresoja; Philipp S Wild; others

Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage

In: Lecture Notes in Computer Science. Medical Image Understanding and Analysis (MIUA-2025), LNCS, Springer Nature, 2025.

Maximilian Hoffmann; Lukas Malburg; Ralph Bergmann

Augmentation of Semantic Processes for Deep Learning Applications

In: Applied Artificial Intelligence, Vol. 39, No. 1, Pages 1-48, Taylor & Francis, 2025.

Timo P. Gros; Nicola Müller; Daniel Höller; Verena Wolf

Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages

In: Workshop on Reliable Data-Driven Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2024), Springer, 2024.