3 papers
cs.RO2026
Diversity You Can Actually Measure: A Fast, Model-Free Diversity Metric for Robotics Datasets
Sreevardhan Sirigiri, Nathan Samuel de Lara, Christopher Agia +2
Robotics datasets for imitation learning typically consist of long-horizon trajectories of different lengths over states, actions, and high-dimensional observations (e.g., RGB vide…
cs.LG2026
SMAC: Score-Matched Actor-Critics for Robust Offline-to-Online Transfer
Nathan Samuel de Lara, Florian Shkurti
Modern offline Reinforcement Learning (RL) methods find performant actor-critics, however, fine-tuning these actor-critics online with value-based RL algorithms typically causes im…
cs.RO2025
STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation
Hossein Goli, Michael Gimelfarb, Nathan Samuel de Lara +3
Off-policy evaluation (OPE) estimates the performance of a target policy using offline data collected from a behavior policy, and is crucial in domains such as robotics or healthca…