Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs. - Junhyung Lyle Kim; Jose Antonio Lara Benitez; Mohammad Taha Toghani; Cameron R. Wolfe; Zhiwei Zhang 001; Anastasios Kyrillidis (CoRR, 2021)

Fine-tuning Neural-Operator architectures for training and generalization. - Jose Antonio Lara Benitez; Takashi Furuya; Florian Faucher; Xavier Tricoche; Maarten V. de Hoop (CoRR, 2023)

Mixture of Experts Soften the Curse of Dimensionality in Operator Learning. - Anastasis Kratsios; Takashi Furuya; Jose Antonio Lara Benitez; Matti Lassas; Maarten V. de Hoop (CoRR, 2024)

Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation. - Jose Antonio Lara Benitez; Takashi Furuya; Florian Faucher; Anastasis Kratsios; Xavier Tricoche; Maarten V. de Hoop (J. Comput. Phys., 2024)

WaveBench: Benchmarking Data-driven Solvers for Linear Wave Propagation PDEs. - Tianlin Liu; Jose Antonio Lara Benitez; Florian Faucher; AmirEhsan Khorashadizadeh; Maarten V. de Hoop; Ivan Dokmanic (Trans. Mach. Learn. Res., 2024)

Neural equilibria for long-term prediction of nonlinear conservation laws. - Jose Antonio Lara Benitez; Junyi Guo; Kareem Hegazy; Ivan Dokmanic; Michael W. Mahoney; Maarten V. de Hoop (CoRR, 2025)