Woojun Kim

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 24

Top Topics

Stochastic Games

Reinforcement Learning

Decision Making Under Uncertainty

Top Venues

Publications

Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making. ICLR (2024)
Samuel Li, Sarthak Bhagat, Joseph Campbell, Yaqi Xie, Woojun Kim, Katia P. Sycara, Simon Stepputtis
ShapeGrasp: Zero-Shot Task-Oriented Grasping with Large Language Models through Geometric Decomposition. CoRR (2024)
Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung
Value-Aided Conditional Supervised Learning for Offline RL. CoRR (2024)
Woojun Kim, Whiyoung Jung, Myungsik Cho, Youngchul Sung
A Variational Approach to Mutual Information-Based Coordination for Multi-Agent Reinforcement Learning. CoRR (2023)
Woojun Kim, Youngchul Sung
Parameter Sharing with Network Pruning for Scalable Multi-Agent Deep Reinforcement Learning. CoRR (2023)
Woojun Kim, Yongjae Shin, Jongeui Park, Youngchul Sung
Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents. CoRR (2023)
Sungho Choi, Seungyul Han, Woojun Kim, Jongseong Chae, Whiyoung Jung, Youngchul Sung
Domain Adaptive Imitation Learning with Visual Observation. CoRR (2023)
Woojun Kim, Jeonghye Kim, Youngchul Sung
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework. ICML (2023)
Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making. CoRR (2023)
Sungho Choi, Seungyul Han, Woojun Kim, Jongseong Chae, Whiyoung Jung, Youngchul Sung
Domain Adaptive Imitation Learning with Visual Observation. NeurIPS (2023)
Woojun Kim, Jeonghye Kim, Youngchul Sung
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework. CoRR (2023)
Woojun Kim, Yongjae Shin, Jongeui Park, Youngchul Sung
Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents. NeurIPS (2023)
Woojun Kim, Whiyoung Jung, Myungsik Cho, Youngchul Sung
A Variational Approach to Mutual Information-Based Coordination for Multi-Agent Reinforcement Learning. AAMAS (2023)
Md. Shahjalal, Woojun Kim, Waqas Khalid, Seokjae Moon, Murad Khan, Shuzhi Liu, Suhyeon Lim, Eunjin Kim, Deok Won Yun, Joohyun Lee, Won Cheol Lee, Seung-Hoon Hwang, Dongkyun Kim, Jang-Won Lee, Heejung Yu, Youngchul Sung, Yeong Min Jang
Enabling technologies for AI empowered 6G massive radio access networks. ICT Express 9 (3) (2023)
Woojun Kim, Youngchul Sung
Parameter Sharing with Network Pruning for Scalable Multi-Agent Deep Reinforcement Learning. AAMAS (2023)
Woojun Kim, Youngchul Sung
An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning. ICML (2023)
Jeewon Jeon, Woojun Kim, Whiyoung Jung, Youngchul Sung
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer. ICML (2022)
Jeewon Jeon, Woojun Kim, Whiyoung Jung, Youngchul Sung
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer. CoRR (2022)
Woojun Kim, Jongeui Park, Youngchul Sung
Communication in Multi-Agent Reinforcement Learning: Intention Sharing. ICLR (2021)
Hyeong-Geol Shin, Jingu Lee, Young Hyun Yun, Seong Ho Yoo, Jinhee Jang, Se Hong Oh, Yoonho Nam, Sehoon Jung, Sunhye Kim, Masaki Fukunaga, Woojun Kim, Hyung Jin Choi, Jongho Lee
χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain. NeuroImage 240 (2021)
Sungho Choi, Seungyul Han, Woojun Kim, Youngchul Sung
Cross-Domain Imitation Learning with a Dual Structure. CoRR (2020)
Woojun Kim, Whiyoung Jung, Myungsik Cho, Youngchul Sung
A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning. CoRR (2020)
Woojun Kim, Myungsik Cho, Youngchul Sung
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning. AAAI (2019)
Woojun Kim, Myungsik Cho, Youngchul Sung
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning. CoRR (2019)