| On quadrature rules for solving partial differential equations using neural networks JA Rivera, JM Taylor, ÁJ Omella, D Pardo Computer Methods in Applied Mechanics and Engineering 393, 114710, 2022 | 38 | 2022 |
| A deep Fourier residual method for solving PDEs using neural networks JM Taylor, D Pardo, I Muga Computer Methods in Applied Mechanics and Engineering 405, 115850, 2023 | 34 | 2023 |
| Convex integration arising in the modelling of shape-memory alloys: some remarks on rigidity, flexibility and some numerical implementations A Rüland, JM Taylor, C Zillinger Journal of Nonlinear Science 29, 2137-2184, 2019 | 22 | 2019 |
| Density functional theory for dense nematic liquid crystals with steric interactions ES Nascimento, P Palffy-Muhoray, JM Taylor, EG Virga, X Zheng Physical Review E 96 (2), 022704, 2017 | 18 | 2017 |
| Maximum Entropy Methods as the Bridge Between Microscopic and Macroscopic Theory JM Taylor Journal of Statistical Physics 164 (6), 1429–1459, 2016 | 10 | 2016 |
| Adaptive Deep Fourier Residual method via overlapping domain decomposition JM Taylor, M Bastidas, VM Calo, D Pardo Computer Methods in Applied Mechanics and Engineering 427, 116997, 2024 | 8 | 2024 |
| Oseen–Frank-type theories of ordered media as the -limit of a non-local mean-field free energy JM Taylor Mathematical Models and Methods in Applied Sciences 28 (04), 615-657, 2018 | 7 | 2018 |
| Deep Fourier Residual method for solving time-harmonic Maxwell's equations JM Taylor, M Bastidas, D Pardo, I Muga Journal of Computational Physics 523, 113623, 2025 | 6 | 2025 |
| Multimodal variational autoencoder for inverse problems in geophysics: application to a 1-D magnetotelluric problem O Rodriguez, JM Taylor, D Pardo Geophysical Journal International 235 (3), 2598-2613, 2023 | 5 | 2023 |
| Leaky cell model of hard spheres TG Fai, JM Taylor, EG Virga, X Zheng, P Palffy-Muhoray The Journal of chemical physics 154 (10), 2021 | 5 | 2021 |
| Γ-convergence of a mean-field model of a chiral doped nematic liquid crystal to the Oseen–Frank description of cholesterics JM Taylor Nonlinearity 33 (6), 3062, 2020 | 5 | 2020 |
| Machine learning discovery of optimal quadrature rules for isogeometric analysis T Teijeiro, JM Taylor, A Hashemian, D Pardo Computer Methods in Applied Mechanics and Engineering 416, 116310, 2023 | 4 | 2023 |
| An analysis of equilibria in dense nematic liquid crystals JM Taylor SIAM Journal on Mathematical Analysis 50 (2), 1918-1957, 2018 | 4 | 2018 |
| Cavity volume and free energy in many-body systems JM Taylor, TG Fai, EG Virga, X Zheng, P Palffy-Muhoray Journal of Nonlinear Science 31 (5), 87, 2021 | 3 | 2021 |
| Optimizing variational physics-informed neural networks using least squares C Uriarte, M Bastidas, D Pardo, JM Taylor, S Rojas Computers & Mathematics with Applications 185, 76-93, 2025 | 2 | 2025 |
| Regularity-conforming neural networks (ReCoNNs) for solving partial differential equations JM Taylor, D Pardo, J Muñoz-Matute arXiv preprint arXiv:2405.14110, 2024 | 2 | 2024 |
| On a probabilistic model for martensitic avalanches incorporating mechanical compatibility F Della Porta, A Rüland, JM Taylor, C Zillinger Nonlinearity 34 (7), 4844, 2021 | 2 | 2021 |
| A Least-Squares-Based Neural Network (LS-Net) for Solving Linear Parametric PDEs S Baharlouei, JM Taylor, C Uriarte, D Pardo Computer Methods in Applied Mechanics and Engineering 437, 117757, 2025 | 1 | 2025 |
| Interaction energies in paranematic colloids D Golovaty, J Taylor, R Venkatraman, A Zarnescu arXiv preprint arXiv:2308.06331, 2023 | 1 | 2023 |
| Memory-Based Monte Carlo Integration for Solving Partial Differential Equations Using Neural Networks C Uriarte, JM Taylor, D Pardo, OA Rodríguez, P Vega International Conference on Computational Science, 509-516, 2023 | 1 | 2023 |
Peter Palffy-MuhorayProfessor, Chemical Physics, Liquid Crystal Institute, Kent State UniversityPreverjeni e-poštni naslov na kent.edu