Deep Gaussian Process Emulation using Stochastic Imputation

07/04/2021
by   Deyu Ming, et al.
0

We propose a novel deep Gaussian process (DGP) inference method for computer model emulation using stochastic imputation. By stochastically imputing the latent layers, the approach transforms the DGP into the linked GP, a state-of-the-art surrogate model formed by linking a system of feed-forward coupled GPs. This transformation renders a simple while efficient DGP training procedure that only involves optimizations of conventional stationary GPs. In addition, the analytically tractable mean and variance of the linked GP allows one to implement predictions from DGP emulators in a fast and accurate manner. We demonstrate the method in a series of synthetic examples and real-world applications, and show that it is a competitive candidate for efficient DGP surrogate modeling in comparison to the variational inference and the fully-Bayesian approach. A package implementing the method is also produced and available at https://github.com/mingdeyu/DGP.

READ FULL TEXT
research
11/03/2017

Structured Variational Inference for Coupled Gaussian Processes

Sparse variational approximations allow for principled and scalable infe...
research
06/02/2023

Linked Deep Gaussian Process Emulation for Model Networks

Modern scientific problems are often multi-disciplinary and require inte...
research
07/20/2022

Machine learning and geospatial methods for large-scale mining data

The canonical technique for nonlinear modeling of spatial and other poin...
research
12/18/2021

GPEX, A Framework For Interpreting Artificial Neural Networks

Machine learning researchers have long noted a trade-off between interpr...
research
12/19/2019

Integrated Emulators for Systems of Computer Models

We generalize the state-of-the-art linked emulator for a system of two c...
research
05/16/2019

Efficient Deep Gaussian Process Models for Variable-Sized Input

Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...
research
12/01/2017

Emulating satellite drag from large simulation experiments

Obtaining accurate estimates of satellite drag coefficients in low Earth...

Please sign up or login with your details

Forgot password? Click here to reset