| A multiscale neural network based on hierarchical nested bases Y Fan, J Feliu-Faba, L Lin, L Ying, L Zepeda-Nśnez Research in the Mathematical Sciences 6 (2), 21, 2019 | 49 | 2019 |
| Meta-learning pseudo-differential operators with deep neural networks J Feliu-Faba, Y Fan, L Ying Journal of computational physics 408, 109309, 2020 | 47 | 2020 |
| Recursively preconditioned hierarchical interpolative factorization for elliptic partial differential equations J Feliu-Fabą, KL Ho, L Ying Communications in Mathematical Sciences 18 (1), 91-108, 2020 | 17 | 2020 |
| A continuous‐discontinuous model for crack branching E Tamayo‐Mas, J Feliu‐Fabą, M Casado‐Antolin, A Rodrķguez‐Ferran International Journal for Numerical Methods in Engineering 120 (1), 86-104, 2019 | 13 | 2019 |
| Learning twitter user sentiments on climate change with limited labeled data A Koenecke, J Feliu-Faba 14th International AAAI Conference on Web and Social media, 2020 | 11 | 2020 |
| Multiscale modelling for the thermal creep analysis of PCM concrete S Mohaine, J Feliu, F Grondin, M Karkri, A Loukili Energy and Buildings 131, 99-112, 2016 | 9 | 2016 |
| Hierarchical interpolative factorization preconditioner for parabolic equations J Feliu-Fabą, L Ying Journal of Scientific Computing 85 (2), 50, 2020 | 7 | 2020 |
| Reinforcement learning in pacman A Gnanasekaran, JF Faba, J An See nalso URL http://cs229. stanford. edu/proj2017/final-reports/5241109. pdf, 2017 | 6 | 2017 |
| Approximate inversion of discrete Fourier integral operators J Feliu-Fabą, L Ying Journal of Computational Physics 446, 110654, 2021 | 1 | 2021 |
| A continuous-discontinusous model to simulate crack branching in quasi-brittle failure J Feliu Fabą Universitat Politčcnica de Catalunya, 2016 | 1 | 2016 |
| Multiscale Algorithms for Structured Matrices: Fast Solvers and Deep Learning JF Fabą Stanford University, 2021 | | 2021 |
