Source time reversal (STR) method for linear elasticity. - Ignacio Brevis; Ángel Rodríguez-Rozas; Jaime H. Ortega; David Pardo (Comput. Math. Appl., 2019)

Data-Driven Finite Elements Methods: Machine Learning Acceleration of Goal-Oriented Computations. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (CoRR, 2020)

A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (Comput. Math. Appl., 2021)

Neural Control of Discrete Weak Formulations: Galerkin, Least-Squares and Minimal-Residual Methods with Quasi-Optimal Weights. - Ignacio Brevis; Ignacio Muga; Kristoffer G. van der Zee (CoRR, 2022)

Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. - Ignacio Brevis; Ignacio Muga; David Pardo; Oscar A. Rodríguez; Kristoffer G. van der Zee (Comput. Math. Appl., 2024)

Neural network methods for power series problems of Perron-Frobenius operators. - T. Udomworarat; Ignacio Brevis; M. Richter; Sergio Rojas; Kristoffer G. van der Zee (CoRR, 2025)