Harley Wiltzer

According to our database, Harley Wiltzer authored at least 11 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

On the geometry and topology of representations: the manifolds of modular addition.

Gabriela Moisescu-Pareja, Gavin McCracken, Harley Wiltzer, Vincent Létourneau, Colin Daniels, Doina Precup, Jonathan Love

CoRR, December, 2025

KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning.

Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey

CoRR, December, 2025

Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning.

Yash Jhaveri, Harley Wiltzer, Patrick Shafto, Marc G. Bellemare, David Meger

CoRR, October, 2025

Tractable Representations for Convergent Approximation of Distributional HJB Equations.

Julie Alhosh, Harley Wiltzer, David Meger

CoRR, March, 2025

Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching.

Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Foundations of Multivariate Distributional Reinforcement Learning.

Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning.

Harley Wiltzer, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Simplifying Constraint Inference with Inverse Reinforcement Learning.

Adriana Hugessen, Harley Wiltzer, Glen Berseth

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Distributional Analogue to the Successor Representation.

Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning.

Harley E. Wiltzer, David Meger, Marc G. Bellemare

Proceedings of the International Conference on Machine Learning, 2022