Publications

This is a (mostly) up-to-date list of my recent publications, which you can also find on my Google Scholar page.

2026

Jake Hofgard, “The Geometry of Lee-Yang Tensors,” 2026, arXiv preprint.

Jake Hofgard and Michael Lindsey, “Efficient Mass Matrix Estimation with Gaussian Cooling,” 2026, arXiv preprint.

Jake Hofgard, Asaf Cohen, and Mathieu Laurière, “Operator Learning for Families of Finite-State Mean-Field Games,” 2026, arXiv preprint.

2025

Andrew Mastin, Jake Hofgard, and Jean-Paul Watson, “A Formulation for Power Flow Interdiction with Bounded Big-M Values,” to appear in Mathematical Programming, 2025.

2024

Jake Hofgard, “Convergence Guarantees for Neural Network-Based Hamilton–Jacobi Reachability,” NeurIPS 2024 Workshop on Data-Driven and Differentiable Simulations, Surrogates, and Solvers (D3S3), 2024, OpenReview.

Jake Hofgard, Jingruo Sun, and Asaf Cohen, “Convergence of the Deep Galerkin Method for Mean Field Control Problems,” to appear in SIAM Journal on Mathematics of Data Science, 2024, arXiv preprint.