A Fast MBO Scheme for Multiclass Data Classification. - Matt Jacobs (SSVM, 2017)

Kernels with prescribed surface tension & mobility for threshold dynamics schemes. - Selim Esedoglu; Matt Jacobs; Pengbo Zhang (J. Comput. Phys., 2017)

Convolution Kernels and Stability of Threshold Dynamics Methods. - Selim Esedoglu; Matt Jacobs (SIAM J. Numer. Anal., 2017)

Auction dynamics: A volume constrained MBO scheme. - Matt Jacobs; Ekaterina Merkurjev; Selim Esedoglu (J. Comput. Phys., 2018)

Solving Large-Scale Optimization Problems with a Convergence Rate Independent of Grid Size. - Matt Jacobs; Flavien Léger; Wuchen Li; Stanley J. Osher (SIAM J. Numer. Anal., 2019)

The back-and-forth method for Wasserstein gradient flows. - Matt Jacobs; Wonjun Lee 004; Flavien Léger (CoRR, 2020)

A fast approach to optimal transport: the back-and-forth method. - Matt Jacobs; Flavien Léger (Numerische Mathematik, 2020)

On the existence of solutions to adversarial training in multiclass classification. - Nicolás García Trillos; Matt Jacobs; Jakwang Kim (CoRR, 2023)

It begins with a boundary: A geometric view on probabilistically robust learning. - Leon Bungert; Nicolás García Trillos; Matt Jacobs; Daniel McKenzie; Dorde Nikolic; Qingsong Wang (CoRR, 2023)

The multimarginal optimal transport formulation of adversarial multiclass classification. - Nicolás García Trillos; Matt Jacobs; Jakwang Kim (J. Mach. Learn. Res., 2023)

Existence of Solutions to Reaction Cross Diffusion Systems. - Matt Jacobs (SIAM J. Math. Anal., 2023)

An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification. - Nicolás García Trillos; Matt Jacobs; Jakwang Kim; Matthew Werenski (CoRR, 2024)

Optimal transport of linear systems over equilibrium measures. - Karthik Elamvazhuthi; Matt Jacobs (Autom., 2025)

Lagrangian Solutions to the Porous Media Equation and Reaction Diffusion Systems. - Matt Jacobs (SIAM J. Math. Anal., 2025)

Asymptotic Linear Convergence of ADMM for Isotropic TV Norm Compressed Sensing. - Emmanuel Gil Torres; Matt Jacobs; Xiangxiong Zhang (CoRR, 2025)