gpplus 0.1.0.0

Python library for Generalized Gaussian Process Modeling

gpplus

GPPlus library

Overview

GPPlus is a Python library that provides generalized Gaussian Process modeling. This repository contains the source code and documentation for the library.

Installation

To install the package, follow these steps:

1. Clone the repository:

   git clone https://github.com/Bostanabad-Research-Group/gp-private.git

2. Navigate to the gp-private directory:

   cd gp-private

3. Install the package using pip:

   pip install .

Usage

After installation, you can import and use the library in your Python scripts. For example:

import gpplus # or the appropriate module name ''' Your code here using gpplus '''

Contributing

We welcome contributions from the community! Please, check our contributing guideline.

More About GP+

GP+ is an open-source library for kernel-based learning via Gaussian processes (GPs). It systematically integrates nonlinear manifold learning techniques with GPs for single and multi-fidelity emulation, calibration of computer models, sensitivity analysis, and Bayesian optimization. GP+ is built on PyTorch and provides a user-friendly and object-oriented tool for probabilistic learning and inference.

For more detailed information, refer to our paper: "GP+: A Python Library for Kernel-based Learning via Gaussian Processes".

Citing Us

If you use GP+ in your work, please use the following citation:

Yousefpour, Amin; Zanjani Foumani, Zahra; Shishehbor, Mehdi; Mora, Carlos; Bostanabad, Ramin. "GP+: A Python Library for Kernel-based Learning via Gaussian Processes." Advances in Engineering Software (2024). https://doi.org/10.1016/j.advengsoft.2024.103686.

License

MIT License