GP+

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Python Library for Generalized Gaussian Process Modeling

Installation

Requirements:

• Python == 3.9
• CUDA >= 11.6 (if using GPU)

To use GP+, you first need to install the specific versions of PyTorch. The installation process involves two steps: (1) installing the specific version of PyTorch based on your system, and (2) installing GP+.

(1) Install PyTorch

For macOS

To install PyTorch for macOS, use:

pip install torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1

For Linux and Windows

To install PyTorch for Linux and Windows, follow the steps below based on whether you have CUDA support or not.

For GPU Support (with CUDA)

If you have a compatible GPU and want to leverage GPU acceleration, install PyTorch with CUDA support:

pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116

For CPU Only

If you do not have a compatible GPU, install the CPU-only version of PyTorch:

pip install torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cpu

(2) Install GP+

Once you have installed the appropriate version of PyTorch, install GP+ using pip:

pip install gpplus

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".

The Team

Amin Yousefpour
Zahra Zanjani Foumani
Mehdi Shishehbor
Carlos Mora
Ramin Bostanabad

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.

Assistance and Support

Need help with GP+? Feel free to open an issue on our GitHub page and label it according to the module or feature in question for quicker assistance.