| Acoustic anomaly detection for machine sounds based on image transfer learning R Müller, F Ritz, S Illium, C Linnhoff-Popien Proceedings of the 13th International Conference on Agents and Artificial …, 2020 | 25 | 2020 |
| Acoustic Leak Detection in Water Networks R Müller, S Illium, F Ritz, T Schröder, C Platschek, J Ochs, ... Proceedings of the 13th International Conference on Agents and Artificial …, 2021 | 12 | 2021 |
| Visual Transformers for Primates Classification and Covid Detection S Illium, R Müller, A Sedlmeier, CL Popien Proc. Interspeech 2021, 451-455, 2021 | 10 | 2021 |
| Policy Entropy for Out-of-Distribution Classification A Sedlmeier, R Müller, S Illium, C Linnhoff-Popien ICANN 2020, 2020 | 10 | 2020 |
| Analysis of Feature Representations for Anomalous Sound Detection R Müller, S Illium, F Ritz, K Schmid Proceedings of the 13th International Conference on Agents and Artificial …, 2020 | 9 | 2020 |
| Surgical Mask Detection with Convolutional Neural Networks and Data Augmentations on Spectrograms S Illium, R Müller, A Sedlmeier, C Linnhoff-Popien INTERSPEECH 2020, 2052-2056, 2020 | 9 | 2020 |
| Stochastic market games K Schmid, L Belzner, R Müller, J Tochtermann, C Linhoff-Popien Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 6 | 2021 |
| A quantum annealing algorithm for finding pure Nash equilibria in graphical games C Roch, T Phan, S Feld, R Müller, T Gabor, C Hahn, C Linnhoff-Popien Computational Science–ICCS 2020: 20th International Conference, Amsterdam …, 2020 | 6 | 2020 |
| SAT-MARL: specification aware training in multi-agent reinforcement learning F Ritz, T Phan, R Müller, T Gabor, A Sedlmeier, M Zeller, J Wieghardt, ... arXiv preprint arXiv:2012.07949, 2020 | 3 | 2020 |
| Towards ecosystem management from greedy reinforcement learning in a predator-prey setting F Ritz, F Hohnstein, R Müller, T Phan, T Gabor, C Hahn, ... Artificial Life Conference Proceedings 32, 518-525, 2020 | 3 | 2020 |
| Difficulty Classification of Mountainbike Downhill Trails utilizing Deep Neural Networks S Langer, R Müller, K Schmid, C Linnhoff-Popien Machine Learning and Knowledge Discovery in Databases 1168, 270-280, 2020 | 3 | 2020 |
| Deep Neural Baselines for Computational Paralinguistics D Elsner, S Langer, F Ritz, R Mueller, S Illium INTERSPEECH 2019, 2019 | 3 | 2019 |
| Specification aware multi-agent reinforcement learning F Ritz, T Phan, R Müller, T Gabor, A Sedlmeier, M Zeller, J Wieghardt, ... Agents and Artificial Intelligence: 13th International Conference, ICAART …, 2022 | 2 | 2022 |
| Towards Anomaly Detection in Reinforcement Learning R Müller, S Illium, T Phan, T Haider, C Linnhoff-Popien Proceedings of the 21st International Conference on Autonomous Agents and …, 2022 | 2 | 2022 |
| A Deep and Recurrent Architecture for Primate Vocalization Classification R Müller, S Illium, C Linnhoff-Popien Proc. Interspeech 2021, 461-465, 2021 | 2 | 2021 |
| Distributed emergent agreements with deep reinforcement learning K Schmid, R Müller, L Belzner, J Tochtermann, C Linhoff-Popien 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 1 | 2021 |
| Deep recurrent interpolation networks for anomalous sound detection R Müller, S Illium, C Linnhoff-Popien 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 1 | 2021 |
| What to do in the meantime: A service coverage analysis for parked autonomous vehicles S Illium, PA Friese, R Müller, S Feld AGILE: GIScience Series 1, 7, 2020 | 1 | 2020 |
| Adaptive Thompson sampling stacks for memory bounded open-loop planning T Phan, T Gabor, R Müller, C Roch, C Linnhoff-Popien 28th International Joint Conference on Artificial Intelligence, 5607-5613, 2019 | 1 | 2019 |
| Case-Based Inverse Reinforcement Learning Using Temporal Coherence J Nüßlein, S Illium, R Müller, T Gabor, C Linnhoff-Popien Case-Based Reasoning Research and Development: 30th International Conference …, 2022 | | 2022 |
Prof. Dr. Claudia Linnhoff-PopienLudwig-Maximilians-University, Mobile and Distributed Systems Group, LMUBestätigte E-Mail-Adresse bei ifi.lmu.de
