| Bayesian reinforcement learning via deep, sparse sampling D Grover, D Basu, C Dimitrakakis International Conference on Artificial Intelligence and Statistics, 3036-3045, 2020 | 9 | 2020 |
| Adaptive belief discretization for POMDP planning D Grover, C Dimitrakakis arXiv preprint arXiv:2104.07276, 2021 | 7 | 2021 |
| Inferential induction: A novel framework for bayesian reinforcement learning E Jorge, H Eriksson, C Dimitrakakis, D Basu, D Grover PMLR, 2020 | 7 | 2020 |
| VISUALIZING THE INDIAN STOCK MARKET: AComplex NETWORKS APPROACH MS Mohamed Rehan, MH Haran, NS Chauhan, D Grover International Journal of Advances in Engineering & Technology, 2013 | 4 | 2013 |
| Minimax-bayes reinforcement learning TK Buening, C Dimitrakakis, H Eriksson, D Grover, E Jorge International Conference on Artificial Intelligence and Statistics, 7511-7527, 2023 | 2 | 2023 |
| On Bayesian Value Function Distributions. E Jorge, H Eriksson, C Dimitrakakis, D Basu, D Grover | | 2022 |
| Efficient Bayesian Planning D Grover PQDT-Global, 2022 | | 2022 |
| Sample Efficient Bayesian Reinforcement Learning D Grover PQDT-Global, 2020 | | 2020 |
| Co-Training and Its Evolved Techniques Theory and Practice VUT Bach, G Divya, NGOHOA Khoa | | 2017 |
Christos DimitrakakisProfessor, University of NeuchatelVerified email at alumni.epfl.ch
