| Population-Guided Parallel Policy Search for Reinforcement Learning W Jung, G Park, Y Sung International Conference on Learning Representations, 2020 | 46 | 2020 |
| MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer J Jeon, W Kim, W Jung, Y Sung International Conference on Machine Learning, 10041-10052, 2022 | 29 | 2022 |
| A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning W Kim, W Jung, M Cho, Y Sung arXiv preprint arXiv:2006.02732, 2020 | 15 | 2020 |
| Robust Imitation Learning against Variations in Environment Dynamics J Chae, S Han, W Jung, M Cho, S Choi, Y Sung International Conference on Machine Learning, 2828-2852, 2022 | 9 | 2022 |
| Multi-task Reinforcement Learning with Task Representation Method M Cho, W Jung, Y Sung ICLR 2022 Workshop on Generalizable Policy Learning in Physical World, 2022 | 5 | 2022 |
| A Variational Approach to Mutual Information-Based Coordination for Multi-Agent Reinforcement Learning W Kim, W Jung, M Cho, Y Sung ICML 2022 Workshop AI for Agent-Based Modelling, 0 | 5* | |
| Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability W Jung, M Cho, J Park, Y Sung Neural Information Processing Systems, 2022 | 3 | 2022 |
| Domain Adaptive Imitation Learning with Visual Observation S Choi, S Han, W Kim, J Chae, W Jung, Y Sung Thirty-seventh Conference on Neural Information Processing Systems, 2023 | | 2023 |
| Model Ensemble-Based Intrinsic Reward for Sparse Reward Reinforcement Learning G Park, W Jung, S Choi, Y Sung | | 2019 |
Youngchul SungProfessor, Electrical Engineering, KAISTVerified email at ee.kaist.ac.kr
