| Coordinated deep reinforcement learners for traffic light control E van der Pol, FA Oliehoek NeurIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016 | 631 | 2016 |
| Contrastive Learning of Structured World Models T Kipf, E van der Pol, M Welling International Conference on Learning Representations (ICLR), 2019 | 333 | 2019 |
| Geometric and Physical Quantities improve E (3) Equivariant Message Passing J Brandstetter, R Hesselink, E van der Pol, E Bekkers, M Welling International Conference on Learning Representations (ICLR), 2022 | 241 | 2022 |
| MDP homomorphic networks: Group symmetries in reinforcement learning E van der Pol, D Worrall, H van Hoof, F Oliehoek, M Welling Advances in Neural Information Processing Systems (NeurIPS), 2020 | 173 | 2020 |
| Hyperspherical Prototype Networks P Mettes, E van der Pol, CGM Snoek Advances in Neural Information Processing Systems (NeurIPS), 2019 | 161 | 2019 |
| Deep reinforcement learning for coordination in traffic light control E Van Der Pol Master's thesis, University of Amsterdam, 2016 | 106 | 2016 |
| Plannable Approximations to MDP Homomorphisms: Equivariance under Actions E van der Pol, T Kipf, FA Oliehoek, M Welling International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020 | 96 | 2020 |
| GANGs: Generative adversarial network games FA Oliehoek, R Savani, J Gallego-Posada, E van der Pol, ED De Jong, ... arXiv preprint arXiv:1712.00679, 2017 | 46 | 2017 |
| Beyond local nash equilibria for adversarial networks FA Oliehoek, R Savani, J Gallego, E Pol, R Groß Belgian Dutch Conference on Machine Learning (BeneLearn), 2018 | 44 | 2018 |
| Visual rationalizations in deep reinforcement learning for atari games L Weitkamp, E van der Pol, Z Akata Benelux Conference on Artificial Intelligence (BNAIC), 2018 | 30 | 2018 |
| Multi-Agent MDP Homomorphic Networks E van der Pol, H van Hoof, FA Oliehoek, M Welling International Conference on Learning Representations (ICLR), 2022 | 26 | 2022 |
| Maximum class separation as inductive bias in one matrix T Kasarla, GJ Burghouts, M van Spengler, E van der Pol, R Cucchiara, ... Advances in Neural Information Processing Systems (NeurIPS), 2022 | 25 | 2022 |
| Equivariant Networks for Zero-Shot Coordination D Muglich, CS de Witt, E van der Pol, S Whiteson, J Foerster Advances in Neural Information Processing Systems (NeurIPS), 2022 | 21 | 2022 |
| One-shot imitation learning via interaction warping O Biza, S Thompson, KR Pagidi, A Kumar, E van der Pol, R Walters, T Kipf, ... arXiv preprint arXiv:2306.12392, 2023 | 10 | 2023 |
| Linguistic style accommodation in disagreements E Van der Pol, S Gieske, R Fernández Proceedings of the Fifth Joint Conference on Lexical and Computational …, 2016 | 6 | 2016 |
| The impact of negative sampling on contrastive structured world models O Biza, E van der Pol, T Kipf ICML Workshop on Self-Supervised Learning for Reasoning and Perception, 2021 | 3 | 2021 |
| Video demo: Deep reinforcement learning for coordination in traffic light control E van der Pol, FA Oliehoek Benelux Conference on Artificial Intelligence (BNAIC), 2016 | 3 | 2016 |
| Symmetry and structure in deep reinforcement learning E van der Pol | 1 | 2023 |
| Expected Return Symmetries D Muglich, J Forkel, E van der Pol, J Foerster arXiv preprint arXiv:2502.01711, 2025 | | 2025 |
| Physical environment interaction with an equivariant policy M Herman, M Welling, H Van Hoof, E van der Pol, D Worrall, FA Oliehoek US Patent 12,100,198, 2024 | | 2024 |
Frans A. OliehoekAssociate Professor at Delft University of TechnologyAdresse e-mail validée de tudelft.nl