159 Open source projects that are alternatives of or similar to Infer

solution of exercises of the book "probabilistic robotics"

The bookdown version lives here: https://bookdown.org/content/3890

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

Bayesian Data Analysis demos for Python

Efficient, lightweight variational inference and approximation bounds

A Python library that helps data scientists to infer causation rather than observing correlation.

How to do Bayesian statistical modelling using numpy and PyMC3

Projection predictive variable selection

nway -- Bayesian cross-matching of astronomical catalogues

A resource list for causality in statistics, data science and physics

A python module to detect stellar flares using Bayesian model comparison

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

Resources to learn more about Machine Learning and Artificial Intelligence

A Bayesian Analysis Toolkit in Julia

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Distributed Bayesian Entity Resolution in Apache Spark

Bayesian Data Analysis demos for R

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

PyMC3 educational resources

nessai: Nested Sampling with Artificial Intelligence

Paper Reading

Full Bayesian Inference for Hidden Markov Models

Python package for computing the Curie depth from the magnetic anomaly

ggplot2 extension for plotting distributions

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

BlackJAX is a sampling library designed for ease of use, speed and modularity.

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

Pharmaceutical Modeling and Simulation for Nonlinear Mixed Effects (NLME), Quantiative Systems Pharmacology (QsP), Physiologically-Based Pharmacokinetics (PBPK) models mixed with machine learning

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Diffusive Nested Sampling

RStan, the R interface to Stan

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

A collection of Bayesian data analysis recipes using PyMC3

C++ template library for probabilistic programming

Variational autoencoders for collaborative filtering

Modular Probabilistic Programming on MXNet

High-performance Bayesian Data Analysis on the GPU in Clojure

Deep universal probabilistic programming with Python and PyTorch

rstanarm R package for Bayesian applied regression modeling

Bayesian inference with probabilistic programming.

The Microbiome Interpretable Temporal Rule Engine

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Material for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

A high-level Bayesian analysis API written in Python

Particle filtering and sequential parameter inference in Python

A method for variant graph genotyping based on exact alignment of k-mers

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC

The base NIMBLE package for R

A Python package for building Bayesian models with TensorFlow or PyTorch

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Deep Learning over PyTorch

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more