2 papers
math.NA2026
Deep operator learning for efficient sampling from invariant measures of stochastic differential equations
Ling Guo, Lei Li, Jingtong Zhang
We introduce an amortized neural sampler that combines operator learning with flow methods for sampling. It maps SDE coefficient functions to pushforwards from a reference measure…
cs.RO2026
VISTA: Vision-Grounded and Physics-Validated Adaptation of UMI data for VLA Training
Siyuan Yang, Linzheng Guo, Ouyang Lu +10
Universal Manipulation Interface (UMI) enables scalable real-world robot data collection without hardware-specific teleoperation, yet leveraging UMI data to train large-scale Visio…