Hello! I am a M.S./Ph.D. student in Computer Science and Engineering at Seoul National University, and working in Vision & Learning Lab

My research interests are mainly in reinforcement learning (including, but not limited to: better robustness and adaptability to new data or tasks, representation learning, and information-theoretic approaches and analyses).



Constrained GPI for Zero-Shot Transfer in Reinforcement Learning
Jaekyeom Kim, Seohong Park, Gunhee Kim
NeurIPS 2022 (to appear)

Lipschitz-constrained Unsupervised Skill Discovery
Seohong Park, Jongwook Choi*, Jaekyeom Kim*, Honglak Lee, Gunhee Kim (*equal contribution)
ICLR 2022
[paper] [arxiv] [project] [code]
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods
Seohong Park, Jaekyeom Kim, Gunhee Kim
NeurIPS 2021
[paper] [appx] [arxiv] [talk] [code]
Unsupervised Skill Discovery with Bottleneck Option Learning
Jaekyeom Kim*, Seohong Park*, Gunhee Kim (*equal contribution)
ICML 2021
[paper] [appx] [arxiv] [talk] [code]
Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration
Jaekyeom Kim, Minjung Kim, Dongyeon Woo, Gunhee Kim
ICLR 2021
[paper] [arxiv] [talk] [code]
Model-Agnostic Boundary-Adversarial Sampling for Test-Time Generalization in Few-Shot Learning
Jaekyeom Kim, Hyoungseok Kim, Gunhee Kim
ECCV 2020 (Oral)
[paper] [appx] [talk] [code]
EMI: Exploration with Mutual Information
Hyoungseok Kim*, Jaekyeom Kim*, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song (*equal contribution)
ICML 2019 (Long talk)
[paper] [supp] [arxiv] [talk] [code]

Honors & Awards