Practical uncertainty quantification for space-dependent inverse heat conduction problem via ensemble physics-informed neural networks

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

Natural Sciences, Computer Science, Physics +16

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

1993 · 14.3K citations

Computing, Computer Engineering, Computer Science +16

Simple and Scalable Predictive Uncertainty Estimation using Deep\n Ensembles

Balaji Lakshminarayanan, Alexander Pritzel, Charles Blundell · arXiv (Cornell University) · 2016 · 3K citations · Full text

Computing, Computer Science, Machine Learning +13

Inverse problems: A Bayesian perspective

Andrew M. Stuart · Acta Numerica · 2010 · 1.8K citations

Natural Sciences, Mathematics, Bayesian Data Analysis +16

Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks

Sifan Wang, Yujun Teng, Paris Perdikaris · SIAM Journal on Scientific Computing · 2021 · 1.6K citations

Natural Sciences, Computer Science, Physics +14