3 papers
cs.LG2025
Behavior Preference Regression for Offline Reinforcement Learning
Padmanaba Srinivasan, William Knottenbelt
Offline reinforcement learning (RL) methods aim to learn optimal policies with access only to trajectories in a fixed dataset. Policy constraint methods formulate policy learning a…
cs.LG2024
CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival Analysis
William Knottenbelt, William McGough, Rebecca Wray +5
Motivation: Survival analysis is a branch of statistics that is crucial in medicine for modeling the time to critical events such as death or relapse, in order to improve treatment…
cs.LG2024
Offline Model-Based Reinforcement Learning with Anti-Exploration
Padmanaba Srinivasan, William Knottenbelt
Model-based reinforcement learning (MBRL) algorithms learn a dynamics model from collected data and apply it to generate synthetic trajectories to enable faster learning. This is a…