| Visualizing and understanding atari agents S Greydanus, A Koul, J Dodge, A Fern International conference on machine learning, 1792-1801, 2018 | 517 | 2018 |
| Explainable Reinforcement Learning via Reward Decomposition Z Juozapaitis, A Koul, A Fern, M Erwig, F Doshi-Velez | 330 | 2019 |
| Learning finite state representations of recurrent policy networks A Koul, S Greydanus, A Fern arXiv preprint arXiv:1811.12530, 2018 | 122 | 2018 |
| ma-gym: Collection of multi-agent environments based on OpenAI gym A Koul https://github.com/koulanurag/ma-gym, 2019 | 44 | 2019 |
| Re-understanding finite-state representations of recurrent policy networks MH Danesh, A Koul, A Fern, S Khorram International conference on machine learning, 2388-2397, 2021 | 32 | 2021 |
| Explaining deep adaptive programs via reward decomposition M Erwig, A Fern, M Murali, A Koul IJCAI/ECAI workshop on explainable artificial intelligence, 2018 | 23 | 2018 |
| Dream and search to control: Latent space planning for continuous control A Koul, VV Kumar, A Fern, S Majumdar arXiv preprint arXiv:2010.09832, 2020 | 5 | 2020 |
| PcLast: Discovering plannable continuous latent states A Koul, S Sujit, S Chen, B Evans, L Wu, B Xu, R Chari, R Islam, R Seraj, ... arXiv preprint arXiv:2311.03534, 2023 | 2 | 2023 |
| SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion G Ma, A Koul, Q Chen, Y Wu, S Kuhar, Y Yu, A Sengupta, V Kumar, ... arXiv preprint arXiv:2510.17925, 2025 | | 2025 |
| Investigating Latent State and Uncertainty Representations in Reinforcement Learning A Koul | | 2022 |
| Offline Policy Comparison with Confidence: Benchmarks and Baselines A Koul, M Phielipp, A Fern arXiv preprint arXiv:2205.10739, 2022 | | 2022 |
| Towards Real-World Offline Reinforcement Learning A Koul, J Dao, A Saxena, R Jayaraman | | |
Alan FernOregon State UniversityVerified email at oregonstate.edu
