Xuhui Meng

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 25

Top Topics

Differential Equations

Dynamical Systems

Top Venues

J. Comput. Phys.

AAAI Spring Symposium: MLPS

Publications

Zongren Zou, Xuhui Meng, Apostolos F. Psaros, George E. Karniadakis
NeuralUQ: A Comprehensive Library for Uncertainty Quantification in Neural Differential Equations and Operators. SIAM Rev. 66 (1) (2024)
Zongren Zou, Xuhui Meng, George Em Karniadakis
Correcting model misspecification in physics-informed neural networks (PINNs). J. Comput. Phys. 505 (2024)
Zhiping Mao, Xuhui Meng
Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving PDEs with sharp solutions. CoRR (2023)
Apostolos F. Psaros, Xuhui Meng, Zongren Zou, Ling Guo, George Em Karniadakis
Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons. J. Comput. Phys. 477 (2023)
Zongren Zou, Xuhui Meng, George Em Karniadakis
Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators. CoRR (2023)
Minglei Lu, Ali Mohammadi, Zhaoxu Meng, Xuhui Meng, Gang Li, Zhen Li
Deep neural operator for learning transient response of interpenetrating phase composites subject to dynamic loading. CoRR (2023)
Kamaljyoti Nath, Xuhui Meng, Daniel J. Smith, George Em Karniadakis
Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines. CoRR (2023)
Xuhui Meng
Variational inference in neural functional prior using normalizing flows: Application to differential equation and operator learning problems. CoRR (2023)
Zongren Zou, Xuhui Meng, George Em Karniadakis
Correcting model misspecification in physics-informed neural networks (PINNs). CoRR (2023)
Kevin Linka, Amelie Schafer, Xuhui Meng, Zongren Zou, George Em Karniadakis, Ellen Kuhl
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems. CoRR (2022)
Apostolos F. Psaros, Xuhui Meng, Zongren Zou, Ling Guo, George Em Karniadakis
Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and Comparisons. CoRR (2022)
Zongren Zou, Xuhui Meng, Apostolos F. Psaros, George Em Karniadakis
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators. CoRR (2022)
Xuhui Meng, Liu Yang, Zhiping Mao, José del Águila Ferrandis, George Em Karniadakis
Learning functional priors and posteriors from data and physics. J. Comput. Phys. 457 (2022)
Jeremy Yu, Lu Lu, Xuhui Meng, George Em Karniadakis
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems. CoRR (2021)
Xuhui Meng, Liu Yang, Zhiping Mao, José del Águila Ferrandis, George Em Karniadakis
Learning Functional Priors and Posteriors from Data and Physics. CoRR (2021)
Xuhui Meng, Hessam Babaee, George Em Karniadakis
Multi-fidelity Bayesian neural networks: Algorithms and applications. J. Comput. Phys. 438 (2021)
Qin Lou, Xuhui Meng, George Em Karniadakis
Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulation. J. Comput. Phys. 447 (2021)
Liu Yang, Xuhui Meng, George Em Karniadakis
B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data. J. Comput. Phys. 425 (2021)
Lu Lu, Xuhui Meng, Zhiping Mao, George Em Karniadakis
DeepXDE: A Deep Learning Library for Solving Differential Equations. SIAM Rev. 63 (1) (2021)
Xuhui Meng, George Em Karniadakis
A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems. J. Comput. Phys. 401 (2020)
Xuhui Meng, Hessam Babaee, George Em Karniadakis
Multi-fidelity Bayesian Neural Networks: Algorithms and Applications. CoRR (2020)
Lu Lu, Xuhui Meng, Zhiping Mao, George Em Karniadakis
DeepXDE: A Deep Learning Library for Solving Differential Equations. AAAI Spring Symposium: MLPS (2020)
Liu Yang, Xuhui Meng, George Em Karniadakis
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data. CoRR (2020)
Lu Lu, Xuhui Meng, Zhiping Mao, George E. Karniadakis
DeepXDE: A deep learning library for solving differential equations. CoRR (2019)
Xuhui Meng, Zhen Li, Dongkun Zhang, George Em Karniadakis
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs. CoRR (2019)