168 Open source projects that are alternatives of or similar to kernel-ep

Tree Approximate Message Passing

Single-cell copy number calling and event history reconstruction.

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

Bayesian Evolutionary Analysis by Sampling Trees

Probabilistic Programming with Gaussian processes in Julia

Statistical Rethinking course in pymc3

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

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

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

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

An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Companion package for the Coursera Statistics with R specialization

NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.

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

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.

Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al

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

A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Expressions and dataframes with statistical details 📉 📜🔣✅

Scalable inference for a generative model of astronomical images

MrBayes is a program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models. For documentation and downloading the program, please see the home page:

Blang's software development kit

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

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

TAPAS - Translational Algorithms for Psychiatry-Advancing Science

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

Transformations to contrained variables from ℝⁿ.

Probabilistic programming via source rewriting

🐙 Generalized additive models in Python with a Bayesian twist

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

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

Collection of probabilistic models and inference algorithms

A didactic Gaussian process package for researchers in Jax.

ELFI - Engine for Likelihood-Free Inference

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

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.

A python package for graph kernels, graph edit distances, and graph pre-image problem.

shinystan R package and ShinyStan GUI

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

Simulation-based inference in PyTorch

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

Statistical Rethinking (2nd Ed) with Tensorflow Probability

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

A web interface for exploring PyMC3 traces

Statistical Rethinking with PyTorch and Pyro

Sequential Monte Carlo in python

Scalable sparse Bayesian learning for large CS recovery problems

Generalized linear mixed-effect model in Python

Nested Sampling post-processing and plotting

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

NeurIPS 2018. Linear-time model comparison tests.

Fast & scalable MCMC for all your exoplanet needs!

Bayesian spatial analysis

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

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

Multi-core BUGS for fast Bayesian inference of large hierarchical models

Material for a Bayesian statistics workshop

Dirichlet Process K-means

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