Thomy Phan
Zitiert von
Zitiert von
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
Emergent escape-based flocking behavior using multi-agent reinforcement learning
C Hahn, T Phan, T Gabor, L Belzner, C Linnhoff-Popien
arXiv preprint arXiv:1905.04077, 2019
Leveraging statistical multi-agent online planning with emergent value function approximation
T Phan, L Belzner, T Gabor, K Schmid
arXiv preprint arXiv:1804.06311, 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
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 (4), 457-476, 2020
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
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
Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search.
T Gabor, J Peter, T Phan, C Meyer, C Linnhoff-Popien
IJCAI, 5562-5568, 2019
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
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
Accelerating evolutionary construction tree extraction via graph partitioning
M Friedrich, S Feld, T Phan, PA Fayolle
arXiv preprint arXiv:2008.03669, 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
Nash Equilibria in Multi-Agent Swarms.
C Hahn, T Phan, S Feld, C Roch, F Ritz, A Sedlmeier, T Gabor, ...
ICAART (1), 234-241, 2020
Artificial intelligence—the new revolutionary evolution
T Phan, S Feld, C Linnhoff-Popien
Digitale Welt 4 (1), 7-8, 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
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
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
Foraging swarms using multi-agent reinforcement learning
C Hahn, F Ritz, P Wikidal, T Phan, T Gabor, C Linnhoff-Popien
Artificial Life Conference Proceedings, 333-340, 2020
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
International Conference on Computational Science, 488-501, 2020
Action markets in deep multi-agent reinforcement learning
K Schmid, L Belzner, T Gabor, T Phan
International Conference on Artificial Neural Networks, 240-249, 2018
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