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Bedaywi, M., Rakhsha, A., & Farahmand, A.-M. (août 2024). PID accelerated temporal difference algorithms [Communication écrite]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (25 pages). Lien externe
Hussing, M., Voelcker, C. A., Gilitschenski, I., Farahmand, A.-M., & Eaton, E. (août 2024). Dissecting Deep RL with high update ratios : combatting value divergence [Communication écrite]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (24 pages). Lien externe
Pirmorad, E., Mansouri, F., & Farahmand, A.-M. (décembre 2024). Deep reinforcement learning for online control of stochastic partial differenctial equations [Communication écrite]. 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC, Canada (6 pages). Lien externe
Rakhsha, A., Kemertas, M., Ghavamzadeh, M., & Farahmand, A.-M. (mai 2024). Maximum entropy model correction in reinforcement learning [Présentation]. Dans 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria. Lien externe
Voelcker, C. A., Kastner, T., Gilitschenski, I., & Farahmand, A.-M. (août 2024). When does self-prediction help? Understanding auxiliary tasks in reinforcement learning [Communication écrite]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (31 pages). Lien externe
