Deep Gaussian Process Models for Integrating Multifidelity Experiments with Non-stationary Relationships

This repository contains code for the paper "Deep Gaussian Process Models for Integrating Multifidelity Experiments with Non-stationary Relationships" by Jongwoo Ko and Heeyoung Kim.

Requirements

• This codebase is written for python3.
• To install necessary python packages, run pip install -r requirements.txt.

Training

python train.py --dataset step --num_replicate 10 --low_layer '[1, 2, 1]' --high_layer '[1, 2, 2]'

Arguments

python train.py [-h] [--dataset] [--batch_size] [--num_replicate] [--low_layer] [--high_layer]
                [--low_learning_rate] [--high_learning_rate] [--low_epoch] [--high_epoch]