Python Library for Generalized Gaussian Process Modeling
Requirements:
- Python >= 3.8
- PyTorch >= 1.13.1
- CUDA >= 11.6
Install GP+ using pip:
pip install gpplusGP+ 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".
Amin Yousefpour
Zahra Zanjani Foumani
Mehdi Shishehbor
Carlos Mora
Ramin Bostanabad
To reference GP+ in your academic work, please use the following citation, now available on arXiv:
Yousefpour, Amin; Zanjani Foumani, Zahra; Shishehbor, Mehdi; Mora, Carlos; Bostanabad, Ramin. (2023). "GP+: A Python Library for Kernel-based Learning via Gaussian Processes." arXiv: [arXiv:2312.07694].
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.