212 citations · 335 across the 36 of their papers we have counts for
41 papers
Higher-Order Mean-Field Control Barrier Functions
Levon Nurbekyan, Samy Wu Fung
Mean-field control barrier functions (MF-CBFs) enforce swarm safety through constraints on the agents' distribution. Previous formulations, including applications to stochastic cov…
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…
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…
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…
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…
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…
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…
On the Convergence of Jacobian-Free Backpropagation for Optimal Control Problems with Implicit Hamiltonians
Eric Gelphman, Deepanshu Verma, Nicole Tianjiao Yang +2
Optimal feedback control with implicit Hamiltonians poses a fundamental challenge for learning-based value function methods due to the absence of closed-form optimal control laws.…
Operator Splitting with Hamilton-Jacobi-based Proximals
Nicholas Di, Eric C. Chi, Samy Wu Fung
Operator splitting algorithms are a cornerstone of modern first-order optimization, decomposing complex problems into simpler subproblems solved via proximal operators. However, mo…
End-to-End Training of High-Dimensional Optimal Control with Implicit Hamiltonians via Jacobian-Free Backpropagation
Eric Gelphman, Deepanshu Verma, Nicole Tianjiao Yang +2
Neural network approaches that parameterize value functions have succeeded in approximating high-dimensional optimal feedback controllers when the Hamiltonian admits explicit formu…
A Monte Carlo Approach for Nonsmooth Convex Optimization via Proximal Splitting Algorithms
Nicholas Di, Eric C. Chi, Samy Wu Fung
Operator splitting algorithms are a cornerstone of modern first-order optimization, relying critically on proximal operators as their fundamental building blocks. However, explicit…
A primal-dual price-optimization method for computing equilibrium prices in mean-field games models
Xu Wang, Samy Wu Fung, Levon Nurbekyan
We develop a simple yet efficient Lagrangian method for computing equilibrium prices in a mean-field game price-formation model. We prove that equilibrium prices are optimal in ter…
Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
Zhiwei Zhang, Samy Wu Fung, Anastasios Kyrillidis +2
The Boolean satisfiability (SAT) problem lies at the core of many applications in combinatorial optimization, software verification, cryptography, and machine learning. While state…
Recent Advances in Numerical Solutions for Hamilton-Jacobi PDEs
Tingwei Meng, Siting Liu, Samy Wu Fung +1
Hamilton-Jacobi partial differential equations (HJ PDEs) play a central role in many applications such as economics, physics, and engineering. These equations describe the evolutio…
A Generalization Bound for a Family of Implicit Networks
Samy Wu Fung, Benjamin Berkels
Implicit networks are a class of neural networks whose outputs are defined by the fixed point of a parameterized operator. They have enjoyed success in many applications including…
On Logical Extrapolation for Mazes with Recurrent and Implicit Networks
Brandon Knutson, Amandin Chyba Rabeendran, Michael Ivanitskiy +4
Recent work suggests that certain neural network architectures -- particularly recurrent neural networks (RNNs) and implicit neural networks (INNs) -- are capable of logical extrap…
Mean-Field Control Barrier Functions: A Framework for Real-Time Swarm Control
Samy Wu Fung, Levon Nurbekyan
Control Barrier Functions (CBFs) are an effective methodology to ensure safety and performative efficacy in real-time control applications such as power systems, resource allocatio…
Fast Partial Fourier Transforms for Large-Scale Ptychography
Ricardo Parada, Samy Wu Fung, Stanley Osher
Ptychography is a popular imaging technique that combines diffractive imaging with scanning microscopy. The technique consists of a coherent beam that is scanned across an object i…
A hybrid SIAC -- data-driven post-processing filter for discontinuities in solutions to numerical PDEs
Soraya Terrab, Samy Wu Fung, Jennifer K. Ryan
We present a hybrid filter that is only applied to the approximation at the final time and allows for reducing errors away from a shock as well as near a shock. It is designed for…
Laplace Meets Moreau: Smooth Approximation to Infimal Convolutions Using Laplace's Method
Ryan J. Tibshirani, Samy Wu Fung, Howard Heaton +1
We study approximations to the Moreau envelope -- and infimal convolutions more broadly -- based on Laplace's method, a classical tool in analysis which ties certain integrals to s…
Kernel Expansions for High-Dimensional Mean-Field Control with Non-local Interactions
Alexander Vidal, Samy Wu Fung, Stanley Osher +2
Mean-field control (MFC) problems aim to find the optimal policy to control massive populations of interacting agents. These problems are crucial in areas such as economics, physic…
Structured World Representations in Maze-Solving Transformers
Michael Igorevich Ivanitskiy, Alex F. Spies, Tilman Räuker +9
Transformer models underpin many recent advances in practical machine learning applications, yet understanding their internal behavior continues to elude researchers. Given the siz…
Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin Splitting
Daniel McKenzie, Samy Wu Fung, Howard Heaton
In many applications, a combinatorial problem must be repeatedly solved with similar, but distinct parameters. Yet, the parameters are not directly observed; only contextual da…
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme
Alexander Vidal, Samy Wu Fung, Luis Tenorio +2
A normalizing flow (NF) is a mapping that transforms a chosen probability distribution to a normal distribution. Such flows are a common technique used for data generation and dens…