Hyperspherical Normalization for Scalable Deep Reinforcement Learning

Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone, Jaegul Choo

Reinforcement Learning ICML 2025

Hyperspherical Normalization for Scalable Deep Reinforcement Learning

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno

Reinforcement Learning ICLR 2025 Spotlight

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Test-time Alignment of Diffusion Models without Reward Over-optimization

Sunwoo Kim, Minkyu Kim, Dongmin Park

Vision & Animation ICLR 2025 Spotlight

Test-time Alignment of Diffusion Models without Reward Over-optimization

Do’s and Don’ts: Learning Desirable Skills with Instruction Videos

Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo

Reinforcement Learning NeurIPS 2024

Do’s and Don’ts: Learning Desirable Skills with Instruction Videos

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive

Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song

Reinforcement Learning NeurIPS 2023

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive