activity
20172026
most citedA Hamilton-Jacobi-based Proximal Operator

10 citations · 14 across the 22 of their papers we have counts for

collaborators

40 papers

math.OC2026

Truncated Differentiation Through Primal-Dual Solvers for Inverse Potential Mean-Field Games

Siting Liu, Yat Tin Chow, Samy Wu Fung

We study inverse potential mean-field games (MFGs), in which an unknown spatial inverse-cost (mobility) map is inferred from observed population densities. We solve the forward MFG…

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…

math.OC2026

Implicit Neural Optimal Transport via Fixed-Point Optimization

Yesom Park, Eric Gelphman, Stanley Osher +1

We propose an implicit neural formulation of optimal transport that eliminates adversarial min--max optimization and multi-network architectures commonly used in existing approache…

eess.SY2026

Mean-field control barrier functions for stochastic multi-agent systems

Cinzia Tomaselli, Gian Carlo Maffettone, Samy Wu Fung +2

Many applications involving multi-agent systems require fulfilling safety constraints. Control barrier functions offer a systematic framework to enforce forward invariance of safet…

math.OC2026

A Gauss-Newton Method with No Additional PDE Solves Beyond Gradient Evaluation for Large-Scale PDE-Constrained Inverse Problems

Cash Cherry, Samy Wu Fung, Luis Tenorio +1

Partial Differential Equation (PDE)-constrained optimization problems often take the form of an optimization of an objective function given as a sum of loss terms. Each function or…

cs.LG2026

Probabilistic Gaussian Homotopy: A Probability-Space Continuation Framework for Nonconvex Optimization

Eshed Gal, Samy Wu Fung, Eldad Haber

We introduce Probabilistic Gaussian Homotopy (PGH), a probability-space continuation framework for nonconvex optimization. Unlike classical Gaussian homotopy, which smooths the obj…