34 Open source projects that are alternatives of or similar to Forneylab.jl

Notebooks about Bayesian methods for machine learning

Course on data assimilation (DA)

Bayesian methods in deep learning Summer School

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

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

A collection of Bayesian data analysis recipes using PyMC3

A simple probabilistic programming language.

Probabilistic reasoning and statistical analysis in TensorFlow

rstanarm R package for Bayesian applied regression modeling

High-quality implementations of standard and SOTA methods on a variety of tasks.

🐢 bayesAB: Fast Bayesian Methods for A/B Testing

Implementation of Bayesian Personalized Ranking (BPR) for Multiple Feedback Channels

A common framework for implementing and using log densities for inference.

Regression with Summary Statistics.

An R package and Shiny application to provide API access to the WorldPop Open Population Repository (WOPR)

An unsupervised machine learning algorithm for the segmentation of spatial data sets.

Multiagent reinforcement learning simulation framework - Undergraduate thesis in Mechatronics Engineering at the University of Brasília

Statistical Rethinking course in pymc3

BayesianNonparametrics in julia

🚂 Python API for Emma's Markov Model Algorithms 🚂

Data Assimilation with Python: a Package for Experimental Research

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.

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

shinystan R package and ShinyStan GUI

An easy-to-use interface for measuring uncertainty and robustness.

Probabilistic Inference on Noisy Time Series

Statistical Rethinking with PyTorch and Pyro

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)

A Java Toolbox for Scalable Probabilistic Machine Learning

The base NIMBLE package for R

A Python package for building Bayesian models with TensorFlow or PyTorch

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