25 citations · 25 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Offline Reinforcement Learning with Behavioral Supervisor Tuning
Padmanaba Srinivasan, William Knottenbelt
Offline reinforcement learning (RL) algorithms are applied to learn performant, well-generalizing policies when provided with a static dataset of interactions. Many recent approach…