More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning. - Kaiwen Wang; Owen Oertell; Alekh Agarwal; Nathan Kallus; Wen Sun 002 (ICML, 2024)

REBEL: Reinforcement Learning via Regressing Relative Rewards. - Zhaolin Gao; Jonathan D. Chang; Wenhao Zhan; Owen Oertell; Gokul Swamy; Kianté Brantley; Thorsten Joachims; Drew Bagnell; Jason D. Lee; Wen Sun 002 (NeurIPS, 2024)

TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models. - Kiwoong Yoo; Owen Oertell; Junhyun Lee; Sanghoon Lee; Jaewoo Kang (NeurIPS, 2024)

RL for Consistency Models: Reward Guided Text-to-Image Generation with Fast Inference. - Owen Oertell; Jonathan D. Chang; Yiyi Zhang; Kianté Brantley; Wen Sun 002 (RLJ, 2024)

RL for Consistency Models: Faster Reward Guided Text-to-Image Generation. - Owen Oertell; Jonathan D. Chang; Yiyi Zhang; Kianté Brantley; Wen Sun 002 (CoRR, 2024)

Dataset Reset Policy Optimization for RLHF. - Jonathan D. Chang; Wenhao Zhan; Owen Oertell; Kianté Brantley; Dipendra Misra; Jason D. Lee; Wen Sun 002 (CoRR, 2024)

Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions. - Yiding Chen; Yiyi Zhang; Owen Oertell; Wen Sun (CoRR, 2025)

Efficient Controllable Diffusion via Optimal Classifier Guidance. - Owen Oertell; Shikun Sun; Yiding Chen; Jin Peng Zhou; Zhiyong Wang; Wen Sun (CoRR, 2025)

Scaling Offline RL via Efficient and Expressive Shortcut Models. - Nicolas A. Espinosa Dice; Yiyi Zhang; Yiding Chen; Bradley Guo; Owen Oertell; Gokul Swamy; Kianté Brantley; Wen Sun 002 (CoRR, 2025)