2 papers
cs.LG2026
Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies
Alex Schutz, Nick Hawes, Victor-Alexandru Darvariu
Graph-based world models have recently emerged as a means of learning transitions over relational state representations. However, existing approaches are largely limited to fixed-t…
cs.LG2026
Quantile-Coupled Flow Matching for Distributional Reinforcement Learning
Michael Groom, Victor-Alexandru Darvariu, Lars Kunze +2
Unlike standard expected-return Reinforcement Learning (RL), Distributional RL (DRL) models the full return distribution, making it better-suited for uncertainty-aware and risk-sen…