4 papers
Embodied Learning of Reward for Musculoskeletal Control with Vision Language Models
Saraswati Soedarmadji, Yunyue Wei, Chen Zhang +2
Discovering effective reward functions remains a fundamental challenge in motor control of high-dimensional musculoskeletal systems. While humans can describe movement goals explic…
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji +1
Bayesian optimization is an effective technique for black-box optimization, but its applicability is typically limited to low-dimensional and small-budget problems due to the cubic…
Population Transformer: Learning Population-level Representations of Neural Activity
Geeling Chau, Christopher Wang, Sabera Talukder +5
We present a self-supervised framework that learns population-level codes for arbitrary ensembles of neural recordings at scale. We address key challenges in scaling models with ne…
Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
Yunyue Wei, Zeji Yi, Hongda Li +2
Learning to move is a primary goal for animals and robots, where ensuring safety is often important when optimizing control policies on the embodied systems. For complex tasks such…