Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets

27 October 2020

Papers citing "Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets"

10 / 10 papers shown

Title
Probabilistic Performance-Pattern Decomposition (PPPD): analysis framework and applications to stochastic mechanical systems Ziqi Wang M. Broccardo Junho Song 52 1 0 04 Mar 2020
Probabilistic Learning on Manifolds Christian Soize R. Ghanem 26 23 0 28 Feb 2020
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset Christian Soize R. Ghanem 133 19 0 28 Oct 2019
Entropy-based closure for probabilistic learning on manifolds Christian Soize R. Ghanem Cosmin Safta Xun Huan Zachary P. Vane J. Oefelein G. Lacaze H. Najm Q. Tang X. Chen 31 30 0 21 Mar 2018
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 84 2,059 0 24 Aug 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 67 1,137 0 02 Aug 2017
Deep learning and the Schrödinger equation Kyle Mills M. Spanner Isaac Tamblyn 48 140 0 05 Feb 2017
Machine Learning of Linear Differential Equations using Gaussian Processes M. Raissi George Karniadakis 75 550 0 10 Jan 2017
Data-driven probability concentration and sampling on manifold Christian Soize R. Ghanem DiffM 25 92 0 08 Mar 2016
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo A. Dalalyan Alexandre B. Tsybakov 164 179 0 06 Mar 2009