| Ultra-high resolution 3D imaging of whole cells F Huang, G Sirinakis, ES Allgeyer, LK Schroeder, WC Duim, EB Kromann, ... Cell 166 (4), 1028-1040, 2016 | 275 | 2016 |
| Resilient multi-agent reinforcement learning with adversarial value decomposition T Phan, L Belzner, T Gabor, A Sedlmeier, F Ritz, C Linnhoff-Popien Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11308 …, 2021 | 26 | 2021 |
| Emergent escape-based flocking behavior using multi-agent reinforcement learning C Hahn, T Phan, T Gabor, L Belzner, C Linnhoff-Popien Artificial Life Conference Proceedings, 598-605, 2019 | 26 | 2019 |
| Uncertainty-based out-of-distribution detection in deep reinforcement learning A Sedlmeier, T Gabor, T Phan, L Belzner, C Linnhoff-Popien arXiv preprint arXiv:1901.02219, 2019 | 25 | 2019 |
| The holy grail of quantum artificial intelligence: major challenges in accelerating the machine learning pipeline T Gabor, L Sünkel, F Ritz, T Phan, L Belzner, C Roch, S Feld, ... Proceedings of the IEEE/ACM 42nd international conference on software …, 2020 | 23 | 2020 |
| Learning and testing resilience in cooperative multi-agent systems T Phan, T Gabor, A Sedlmeier, F Ritz, B Kempter, C Klein, H Sauer, ... Proceedings of the 19th International Conference on Autonomous Agents and …, 2020 | 23 | 2020 |
| The scenario coevolution paradigm: adaptive quality assurance for adaptive systems T Gabor, A Sedlmeier, T Phan, F Ritz, M Kiermeier, L Belzner, B Kempter, ... International Journal on Software Tools for Technology Transfer 22, 457-476, 2020 | 21 | 2020 |
| Uncertainty-based out-of-distribution classification in deep reinforcement learning A Sedlmeier, T Gabor, T Phan, L Belzner, C Linnhoff-Popien arXiv preprint arXiv:2001.00496, 2019 | 21 | 2019 |
| Leveraging statistical multi-agent online planning with emergent value function approximation T Phan, L Belzner, T Gabor, K Schmid Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 19 | 2018 |
| Preparing for the unexpected: Diversity improves planning resilience in evolutionary algorithms T Gabor, L Belzner, T Phan, K Schmid 2018 IEEE international conference on autonomic computing (ICAC), 131-140, 2018 | 14 | 2018 |
| Action markets in deep multi-agent reinforcement learning K Schmid, L Belzner, T Gabor, T Phan Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 12 | 2018 |
| Scenario co-evolution for reinforcement learning on a grid world smart factory domain T Gabor, A Sedlmeier, M Kiermeier, T Phan, M Henrich, M Pichlmair, ... Proceedings of the Genetic and Evolutionary Computation Conference, 898-906, 2019 | 11 | 2019 |
| Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search. T Gabor, J Peter, T Phan, C Meyer, C Linnhoff-Popien IJCAI, 5562-5568, 2019 | 11 | 2019 |
| Vast: Value function factorization with variable agent sub-teams T Phan, F Ritz, L Belzner, P Altmann, T Gabor, C Linnhoff-Popien Advances in Neural Information Processing Systems 34, 24018-24032, 2021 | 10 | 2021 |
| Foraging swarms using multi-agent reinforcement learning C Hahn, F Ritz, P Wikidal, T Phan, T Gabor, C Linnhoff-Popien Artificial Life Conference Proceedings 32, 333-340, 2020 | 10 | 2020 |
| Cross entropy hyperparameter optimization for constrained problem Hamiltonians applied to QAOA C Roch, A Impertro, T Phan, T Gabor, S Feld, C Linnhoff-Popien 2020 International Conference on Rebooting Computing (ICRC), 50-57, 2020 | 8 | 2020 |
| Capturing dependencies within machine learning via a formal process model F Ritz, T Phan, A Sedlmeier, P Altmann, J Wieghardt, R Schmid, H Sauer, ... International Symposium on Leveraging Applications of Formal Methods, 249-265, 2022 | 7 | 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 | 7 | 2022 |
| Memory bounded open-loop planning in large pomdps using thompson sampling T Phan, L Belzner, M Kiermeier, M Friedrich, K Schmid, C Linnhoff-Popien Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7941-7948, 2019 | 7 | 2019 |
| Distributed policy iteration for scalable approximation of cooperative multi-agent policies T Phan, K Schmid, L Belzner, T Gabor, S Feld, C Linnhoff-Popien arXiv preprint arXiv:1901.08761, 2019 | 7 | 2019 |
Prof. Dr. Claudia Linnhoff-PopienLudwig-Maximilians-University, Mobile and Distributed Systems Group, LMUVerified email at ifi.lmu.de
