Parametric Gaussian Process Regression for Big Data

11 April 2017

Papers citing "Parametric Gaussian Process Regression for Big Data"

7 / 7 papers shown

Title
Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression S. Z. Ashtiani Mohammad Sarabian K. Laksari H. Babaee 34 2 0 14 Mar 2024
PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator Shaowu Pan E. Kaiser Brian M. de Silva J. Nathan Kutz Steven L. Brunton 21 8 0 22 Jun 2023
Latent Map Gaussian Processes for Mixed Variable Metamodeling Nicholas Oune Ramin Bostanabad 15 32 0 07 Feb 2021
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data M. Raissi A. Yazdani George Karniadakis AI4CE PINN 19 158 0 13 Aug 2018
Machine Learning of Space-Fractional Differential Equations Mamikon A. Gulian M. Raissi P. Perdikaris George Karniadakis 35 46 0 02 Aug 2018
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations M. Raissi 25 183 0 19 Apr 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 28 745 0 20 Jan 2018