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 | 400 | 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 | 215 | 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 | 178 | 2023 |

STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁_{1}-MINIMIZATIONL 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 |

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 |

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 | 47 | 2022 |

Constructing least-squares polynomial approximations L Guo, A Narayan, T Zhou SIAM Review 62 (2), 483-508, 2020 | 47 | 2020 |

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 | 47 | 2018 |

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 | 39 | 2022 |

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 |

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 | 33 | 2018 |

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 |

Data-driven polynomial chaos expansions: A weighted least-square approximation L Guo, Y Liu, T Zhou Journal of Computational Physics 381, 129-145, 2019 | 25 | 2019 |

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 |

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 | 12 | 2022 |

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 |

Stochastic collocation methods via minimization of Transformed penalty L Guo, J Li, Y Liu arXiv preprint arXiv:1805.05416, 2018 | 7 | 2018 |