| Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems D Zhang, L Lu, L Guo, GE Karniadakis Journal of Computational Physics 397, 108850, 2019 | 411 | 2019 |
| Learning in modal space: Solving time-dependent stochastic PDEs using physics-informed neural networks D Zhang, L Guo, GE Karniadakis SIAM Journal on Scientific Computing 42 (2), A639-A665, 2020 | 219 | 2020 |
| Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons AF Psaros, X Meng, Z Zou, L Guo, GE Karniadakis Journal of Computational Physics 477, 111902, 2023 | 192 | 2023 |
| STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁1-MINIMIZATION L Yan, L Guo, D Xiu International Journal for Uncertainty Quantification 2 (3), 2012 | 149 | 2012 |
| H 1-Galerkin mixed finite element method for the regularized long wave equation L Guo, H Chen Computing 77 (2), 205-221, 2006 | 86 | 2006 |
| Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations L Guo, H Wu, X Yu, T Zhou Computer Methods in Applied Mechanics and Engineering 400, 115523, 2022 | 53 | 2022 |
| H1-Galerkin mixed finite element method for the Sobolev equation L Guo, HZ Chen Journal of Systems Science and Mathematical Sciences 26 (3), 301-314, 2006 | 53 | 2006 |
| Efficient multistep methods for tempered fractional calculus: algorithms and simulations L Guo, F Zeng, I Turner, K Burrage, GE Karniadakis SIAM Journal on Scientific Computing 41 (4), A2510-A2535, 2019 | 50 | 2019 |
| A gradient enhanced ℓ1-minimization for sparse approximation of polynomial chaos expansions L Guo, A Narayan, T Zhou Journal of Computational Physics 367, 49-64, 2018 | 50 | 2018 |
| Constructing least-squares polynomial approximations L Guo, A Narayan, T Zhou SIAM Review 62 (2), 483-508, 2020 | 48 | 2020 |
| Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models L Guo, H Wu, T Zhou Journal of Computational Physics 461, 111202, 2022 | 41 | 2022 |
| Weighted approximate Fekete points: Sampling for least-squares polynomial approximation L Guo, A Narayan, L Yan, T Zhou SIAM Journal on Scientific Computing 40 (1), A366-A387, 2018 | 34 | 2018 |
| Stochastic Collocation Algorithms Using l_1-Minimization for Bayesian Solution of Inverse Problems L Yan, L Guo SIAM Journal on Scientific Computing 37 (3), A1410-A1435, 2015 | 34 | 2015 |
| Data-driven polynomial chaos expansions: A weighted least-square approximation L Guo, Y Liu, T Zhou Journal of Computational Physics 381, 129-145, 2019 | 27 | 2019 |
| Stochastic Collocation Methods via Minimization Using Randomized Quadratures L Guo, A Narayan, T Zhou, Y Chen SIAM Journal on Scientific Computing 39 (1), A333-A359, 2017 | 27 | 2017 |
| Blood cells as supercarrier systems for advanced drug delivery S Wang, K Han, S Ma, X Qi, L Guo, X Li Medicine in Drug Discovery 13, 100119, 2022 | 14 | 2022 |
| Vibration analysis of Kirchhoff plates by the Morley element method J Huang, L Guo, Z Shi Journal of Computational and Applied Mathematics 213 (1), 14-34, 2008 | 14 | 2008 |
| A Unified Fast Memory-Saving Time-Stepping Method for Fractional Operators and Its Applications. Y Huang, Q Li, R Li, F Zeng, L Guo Numerical Mathematics: Theory, Methods & Applications 15 (3), 2022 | 13 | 2022 |
| Stochastic Collocation via l1-Minimisation on Low Discrepancy Point Sets with Application to Uncertainty Quantification Y Liu, L Guo East Asian Journal on Applied Mathematics 6 (2), 171-191, 2016 | 8 | 2016 |
| Error estimate of the fast L1 method for time-fractional subdiffusion equations Y Huang, F Zeng, L Guo Applied Mathematics Letters 133, 108288, 2022 | 7 | 2022 |
George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and Engineering在 brown.edu 的电子邮件经过验证
