228 Open source projects that are alternatives of or similar to Nimble

library of C++ functions that support applications of Stan in Pharmacometrics

Use MCMC to analyze districting plans and gerrymanders

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

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.

The Python ensemble sampling toolkit for affine-invariant MCMC

Particle filtering and sequential parameter inference in Python

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

🐢 bayesAB: Fast Bayesian Methods for A/B Testing

Deep universal probabilistic programming with Python and PyTorch

Documentation, models and code relating to the 3rd edition of the textbook Stochastic Modelling for Systems Biology

General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

Implementing MCMC sampling from scratch in R for various Bayesian models

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

nessai: Nested Sampling with Artificial Intelligence

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

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

Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz

Efficient, lightweight variational inference and approximation bounds

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

Python package for computing the Curie depth from the magnetic anomaly

Helper functions for brmsfit objects (DEPRECATED)

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

ggplot2 extension for plotting distributions

A multi-planet Radial Velocity and Transit modelling software

Benchmarks of Bayesian Nonparametric models in Turing and other PPLs

Deep Learning over PyTorch

Estimating effective elastic thickness of the lithosphere

A python module to detect stellar flares using Bayesian model comparison

CmdStanR: the R interface to CmdStan

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

MCMC sample analysis, kernel densities, plotting, and GUI

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

Noisy network measurement with stan

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

Machine Learning - accelerated Bayesian inference

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

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

Start with the Chempy tutorial

Generation of Synthetic Populations Library

Boltzmann Machines in TensorFlow with examples

Natural Gradient, Variational Inference

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.

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

Diffusive Nested Sampling

Resources to learn more about Machine Learning and Artificial Intelligence

Data-driven Network-based Bayesian Inference of Drivers

Infer the gender of an individual based on their name.

PhyML -- Phylogenetic estimation using (Maximum) Likelihood

Implementation of normalising flows and constrained random variable transformations

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

solution of exercises of the book "probabilistic robotics"

🎓 Uni-Bonn Decision Analysis graduate course, lectures and materials

Probabilistic Programming with Gaussian processes in Julia

A C++ library of Markov Chain Monte Carlo (MCMC) methods

Deodorant: Solving the problems of Bayesian Optimization

Notebooks about Bayesian methods for machine learning

Course on data assimilation (DA)

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