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"

7 / 7 papers shown

Title
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 38 75 0 07 May 2023
Probabilistic learning constrained by realizations using a weak formulation of Fourier transform of probability measures Christian Soize 18 5 0 06 May 2022
Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints Christian Soize 30 5 0 10 Feb 2022
On the Correspondence between Gaussian Processes and Geometric Harmonics Felix Dietrich J. M. Bello-Rivas Ioannis G. Kevrekidis 31 3 0 05 Oct 2021
Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation Truong-Vinh Hoang S. Krumscheid H. Matthies Raúl Tempone 26 7 0 15 Jun 2021
Latent Map Gaussian Processes for Mixed Variable Metamodeling Nicholas Oune Ramin Bostanabad 21 32 0 07 Feb 2021
Probabilistic Performance-Pattern Decomposition (PPPD): analysis framework and applications to stochastic mechanical systems Ziqi Wang M. Broccardo Junho Song 40 1 0 04 Mar 2020