74 Open source projects that are alternatives of or similar to gp

A minimal implementation of Gaussian process regression in PyTorch

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An easy and fast library to apply gaussian blur filter on any images. 🎩

Python3 project applying Gaussian process regression for forecasting stock trends

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.

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Notebooks about Bayesian methods for machine learning

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customized GPflow with simple Tensorflow API

Fast and flexible Gaussian Process regression in Python

Fast & scalable MCMC for all your exoplanet needs!

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A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

Machine learning, in numpy

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R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.

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Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB

A highly efficient and modular implementation of Gaussian Processes in PyTorch

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Useful tools for periodicity analysis in time series data.

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html

Sparse Gaussian Process Potentials

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

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GPstuff - Gaussian process models for Bayesian analysis

A library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers

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