Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning. - Harley E. Wiltzer; David Meger; Marc G. Bellemare (ICML, 2022)

Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control. - Nate Rahn; Pierluca D'Oro; Harley Wiltzer; Pierre-Luc Bacon; Marc G. Bellemare (NeurIPS, 2023)

A Distributional Analogue to the Successor Representation. - Harley Wiltzer; Jesse Farebrother; Arthur Gretton; Yunhao Tang; André Barreto 001; Will Dabney; Marc G. Bellemare; Mark Rowland 001 (ICML, 2024)

Simplifying Constraint Inference with Inverse Reinforcement Learning. - Adriana Hugessen; Harley Wiltzer; Glen Berseth (NeurIPS, 2024)

Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning. - Harley Wiltzer; Marc G. Bellemare; David Meger; Patrick Shafto; Yash Jhaveri (NeurIPS, 2024)

Foundations of Multivariate Distributional Reinforcement Learning. - Harley Wiltzer; Jesse Farebrother; Arthur Gretton; Mark Rowland 001 (NeurIPS, 2024)

Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. - Arnav Kumar Jain; Harley Wiltzer; Jesse Farebrother; Irina Rish; Glen Berseth; Sanjiban Choudhury (ICLR, 2025)

Tractable Representations for Convergent Approximation of Distributional HJB Equations. - Julie Alhosh; Harley Wiltzer; David Meger (CoRR, 2025)