| Planet of the bayesians: Reconsidering and improving deep planning network by incorporating bayesian inference M Okada, N Kosaka, T Taniguchi 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 41 | 2020 |
| Direct preference-based policy optimization without reward modeling G An, J Lee, X Zuo, N Kosaka, KM Kim, HO Song Advances in Neural Information Processing Systems 36, 70247-70266, 2023 | 26 | 2023 |
| Know your action set: Learning action relations for reinforcement learning A Jain, N Kosaka, KM Kim, JJ Lim International Conference on Learning Representations, 2021 | 17 | 2021 |
| Has it explored enough? N Kosaka Royal Holloway, University of London, 2019 | 3 | 2019 |
| Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions A Jain, N Kosaka, X Li, KM Kim, E Bıyık, JJ Lim arXiv preprint arXiv:2410.11833, 2024 | | 2024 |
| Visualising Dirichlet Domains given Symmetric Polygons N Kosaka | | 2024 |
| Enhancing Actor-Critic Decision-Making with Afterstate Models for Continuous Control N Kosaka ICML 2024 Workshop: Aligning Reinforcement Learning Experimentalists and …, 2024 | | 2024 |
| Rethinking Actor-Critic: Successive Actors for Critic Maximization A Jain, N Kosaka, X Li, KM Kim, JJ Lim | | 2024 |
| Overview of Riemann Surfaces N Kosaka | | 2023 |
| Designing an offline reinforcement learning objective from scratch. G An, J Lee, X Zuo, N Kosaka, KM Kim, HO Song CoRR, 2023 | | 2023 |
| Hedge Your Actions: Flexible Reinforcement Learning for Complex Action Spaces N Kosaka, A Jain, X Li, KM Kim, JJ Lim | | 2023 |
| Introduction to χ-boundedness N Kosaka http://dx.doi.org/10.13140/RG.2.2.26811.90405, 2022 | | 2022 |
Kyungmin KimCLOVA, NAVERAdresse e-mail validée de bi.snu.ac.kr
