Publications
An up to date list can be found on Google Scholar.
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
T. Kastner, M. Rowland, Y. Tang, M. Erdogdu, A.-m. Farahmand. ICML, 2025.
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning
C. Voelcker, T. Kastner, I. Gilitchenski, A.-m. Farahmand. RLC, 2024.
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
T. Kastner, M. Erdogdu, A.-m. Farahmand. NeurIPS, 2023.
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes
P. S. Castro, T. Kastner, P. Panangaden, M. Rowland. TMLR, 2022.
State similarity metrics in reinforcement learning
MSc Thesis, 2022.
MICo: Improved representations via sampling-based state similarity for Markov decision processes
P. S. Castro*, T. Kastner*, P. Panangaden, M. Rowland. NeurIPS, 2021.
