Clustering and Predictions with Multi-Task Gaussian Processes
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Updated
Jun 28, 2024 - R
Clustering and Predictions with Multi-Task Gaussian Processes
A software package for flexible HPC GPs
A python package for surrogate models that interface with calibration and other tools
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
A simple tool to help you with Gaussian calculations
American Sign Language (ASL) Detection using CNN
Repository for Bayesian Optimization with a Gaussian Process surrogate model in python
A highly efficient implementation of Gaussian Processes in PyTorch
Non-parametric density inference for single-cell analysis.
Geostatistical processes for the GeoStats.jl framework
Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
Explore selected topics related to Gaussian processes
Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
R-shiny apps to generate Gaussian processes using Cholesky
Deterministic algorithms for objective Bayesian inference and hyperparameter optimization
Gaussian processes in JAX.
This project aims to implement Shape Transfer Bayesian Optimization, and compare it with other existing transfer Bayesian Optimization Methods.
A Python implementation of global optimization with gaussian processes.
Combining tree-boosting with Gaussian process and mixed effects models
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