| Epistemic risk-sensitive reinforcement learning H Eriksson, C Dimitrakakis The 28th European Symposium on Artificial Neural Networks, Computational …, 2020 | 27 | 2020 |
| Sentinel: Taming uncertainty with ensemble-based distributional reinforcement learning H Eriksson, D Basu, M Alibeigi, C Dimitrakakis The 38th Conference on Uncertainty in Artificial Intelligence, 2021 | 19 | 2021 |
| Inferential induction: Joint bayesian estimation of mdps and value functions C Dimitrakakis, H Eriksson, E Jorge, D Grover, D Basu PMLR, 2020 | 7* | 2020 |
| Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty H Eriksson, D Basu, M Alibeigi, C Dimitrakakis The 13th Workshop on Optimization and Learning in Multiagent Systems @ AAMAS'22, 2022 | 5 | 2022 |
| Minimax-Bayes Reinforcement Learning TK Buening, C Dimitrakakis, H Eriksson, D Grover, E Jorge The 26th International Conference on Artificial Intelligence and Statistics, 2023 | 2 | 2023 |
| Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer H Eriksson, D Basu, T Tram, M Alibeigi, C Dimitrakakis arXiv preprint arXiv:2302.09273, 2023 | 1 | 2023 |
| Robustness During Learning, Interaction and Adaptation for Autonomous Driving H Eriksson | | 2023 |
| Risk-Averse Decision-Making under Parametric Uncertainty H Eriksson Chalmers Tekniska Hogskola (Sweden), 2022 | | 2022 |
| High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling H Eriksson, C Dimitrakakis, L Carlsson arXiv preprint arXiv:2104.11834, 2021 | | 2021 |
| Automated experiment design for drug development H Eriksson | | 2015 |
| Security in access control systems using RFID D Alm, H Eriksson, D Fallstrand, R Karlsson, V Lindström, R Stigsson | | 2014 |
Christos DimitrakakisProfessor, University of NeuchatelVerified email at alumni.epfl.ch
