Reinforcement Learning with Feedback-modulated TD-STDP. - Stephen Chung; Robert Kozma 001 (CoRR, 2020)

An Alternative to Backpropagation in Deep Reinforcement Learning. - Stephen Chung (CoRR, 2020)

Every Hidden Unit Maximizing Output Weights Maximizes The Global Reward. - Stephen Chung (CoRR, 2020)

MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents. - Stephen Chung (NeurIPS, 2021)

Turing Completeness of Bounded-Precision Recurrent Neural Networks. - Stephen Chung; Hava T. Siegelmann (NeurIPS, 2021)

Learning by Competition of Self-Interested Reinforcement Learning Agents. - Stephen Chung (AAAI, 2022)

Domain Generalization for Robust Model-Based Offline Reinforcement Learning. - Alan Clark; Shoaib Ahmed Siddiqui; Robert Kirk; Usman Anwar; Stephen Chung; David Krueger 001 (CoRR, 2022)

Thinker: Learning to Plan and Act. - Stephen Chung; Ivan Anokhin; David Krueger 001 (NeurIPS, 2023)

Structural Credit Assignment with Coordinated Exploration. - Stephen Chung (CoRR, 2023)

Unbiased Weight Maximization. - Stephen Chung (CoRR, 2023)

Predicting Future Actions of Reinforcement Learning Agents. - Stephen Chung; Scott Niekum; David Krueger 001 (NeurIPS, 2024)

Handling Delay in Real-Time Reinforcement Learning. - Ivan Anokhin; Rishav Rishav; Matthew Riemer; Stephen Chung; Irina Rish; Samira Ebrahimi Kahou (ICLR, 2025)

Interpreting Emergent Planning in Model-Free Reinforcement Learning. - Thomas Bush; Stephen Chung; Usman Anwar; Adrià Garriga-Alonso; David Krueger 001 (ICLR, 2025)

Best Practices for Phase Noise Simulations of Free Running Ring Oscillators for Crystal-Free Narrowband FSK Communication Systems. - Haziq Rohail; Stephen Chung; Titan Yuan; David C. Burnett (ISCAS, 2025)

Learning from Failures in Multi-Attempt Reinforcement Learning. - Stephen Chung; Wenyu Du; Jie Fu 001 (CoRR, 2025)

Learning from Peers in Reasoning Models. - Tongxu Luo; Wenyu Du; Jiaxi Bi; Stephen Chung; Zhengyang Tang; Hao Yang 006; Min Zhang; Benyou Wang (CoRR, 2025)

Thinker: Learning to Think Fast and Slow. - Stephen Chung; Wenyu Du; Jie Fu 001 (CoRR, 2025)