Publications
In preparation
- H. Alsobhi, I. Brevis, and K. G. van der Zee, Hybrid neural networks and FEMs for optimizing minimal residuals in first-orders PDEs.
- T. Udomworarat, S. Rojas, I. Brevis, M. Richter, and K. G. van der Zee, Neural networks method for Perron-Frobenius problems
- H. Alsobhi, I. Brevis, D. Kalise, and K. G. van der Zee, TV-regularized least-square FEM for first-order PDEs
- I. Brevis, C. Montoya, and S. Parra, An inverse problems for linear system of coupled wave equations from boundary measurements
Submitted
Published
- E. Elsayed, I. Brevis, S. Pandiyan, R. Wildman, K. G. van der Zee, and B. Tokay, Controlling ZIF-67 film properties in water-based cathodic electrochemical deposition, Journal of Solid State Chemistry, Vol. 338, 2024, pp. 124820.
- I. Brevis, I. Muga, D. Pardo, O. Rodriguez, and K. G. van der Zee, Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach, Computers and Mathematics with Applications, Vol. 164, 2024, pp. 139-149.
- I. Brevis, I. Muga, and K. G. van der Zee, Neural control of discrete weak formulations: Galerkin, least-squares & minimal-residual methods with quasi-optimal weights, Computer Methods in Applied Mechanics and Engineering, Vol. 402, 2022, pp. 115716.
- I. Brevis, I. Muga, and K. G. van der Zee, A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations, Computers and Mathematics with Applications, Vol. 95, 2021, pp. 186-199.
- I. Brevis, A. RodrÃguez-Rozas, J. H. Ortega, and D. Pardo, Source time reversal (STR) method for linear elasticity, Computers and Mathematics with Applications, Vol. 77, Issue 5, 2019, pp. 1358-1375.
- I. Brevis, J. H. Ortega, and D. Pardo, A source time reversal method for seismicity induced by mining, Inverse Problems and Imaging, Vol. 11, Issue 1, 2017, pp. 25-45.
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