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cs.LG2026
End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers
Xingjian Li, Kelvin Kan, Deepanshu Verma +3
We consider the problem of learning high-dimensional semi-global feedback controllers under hard safety constraints enforced by control barrier functions (CBFs). Incorporating CBFs…
cs.LG2026
Physics-conforming Latent Twins
Matthias Chung, Yutong Bu, Deepanshu Verma
Surrogate models are central to scientific machine learning, where they enable fast prediction, simulation, inference, and control for complex physical systems. For time-dependent…
cs.LG2026
Boost Like a (Var)Pro: Trust-Region Gradient Boosting via Variable Projection
Abhijit Chowdhary, Elizabeth Newman, Deepanshu Verma
Gradient boosting, a method of building additive ensembles from weak learners, has established itself as a practical and theoretically-motivated approach to approximate functions,…