255 Open source projects that are alternatives of or similar to GPJax

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

Probabilistic Programming with Gaussian processes in Julia

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

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.

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

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Machine learning, in numpy

Fast and Easy Infinite Neural Networks in Python

The Trendiness of Trends

A Python package for approximate Bayesian inference and optimization using Gaussian processes

Fast & scalable MCMC for all your exoplanet needs!

GPstuff - Gaussian process models for Bayesian analysis

Probabilistic Programming with Gaussian processes in Julia

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

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

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

Tree Approximate Message Passing

"Learning Machine Learning" Course, Bogotá, Colombia 2019 #LML2019

Pure Python, MIT-licensed implementation of nested sampling algorithms for evaluating Bayesian evidence.

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Unofficial JAX implementations of deep learning research papers

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

customized GPflow with simple Tensorflow API

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

Graphsignal Python agent

ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.

Revisiting Rainbow

Scalable sparse Bayesian learning for large CS recovery problems

A GPT, made only of MLPs, in Jax

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

Library of composable generative population models which serve as the modeling and inference backend of BayesDB.

🐙 Generalized additive models in Python with a Bayesian twist

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Statistical Rethinking course in pymc3

Separating Normalizing Flows code from Pyro and improving API

A web interface for exploring PyMC3 traces

Companion package for the Coursera Statistics with R specialization

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Nested Sampling post-processing and plotting

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022

Blang's software development kit

Computational Fluid Dynamics in JAX

Probabilistic programming via source rewriting

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

Collection of probabilistic models and inference algorithms

Bayesian spatial analysis

PyRate is a program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework.

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

ELFI - Engine for Likelihood-Free Inference

Differentiable Gaussian Process implementation for PyTorch

Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al

Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

Simultaneous Localization and Mapping(SLAM) also gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features.

Dirichlet Process K-means

JAX implementations of core Deep RL algorithms

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.