167 Open source projects that are alternatives of or similar to LDA_thesis

A Latent Dirichlet Allocation implementation in Python.

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

Probabilistic programming via source rewriting

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 approximate Bayesian inference and optimization using Gaussian processes

Bayesian spatial analysis

Collection of probabilistic models and inference algorithms

Nested Sampling post-processing and plotting

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

Simulation-based inference in PyTorch

Scalable inference for a generative model of astronomical images

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

A web interface for exploring PyMC3 traces

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

A didactic Gaussian process package for researchers in Jax.

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

Transformations to contrained variables from ℝⁿ.

ELFI - Engine for Likelihood-Free Inference

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

shinystan R package and ShinyStan GUI

Statistical Rethinking course in pymc3

Statistical Rethinking (2nd Ed) with Tensorflow Probability

🐙 Generalized additive models in Python with a Bayesian twist

Single-cell copy number calling and event history reconstruction.

Sequential Monte Carlo in python

Generalized linear mixed-effect model in Python

Scalable sparse Bayesian learning for large CS recovery problems

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

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

Gibbs sampler for the Hierarchical Latent Dirichlet Allocation topic model

Separating Normalizing Flows code from Pyro and improving API

Blang's software development kit

Companion package for the Coursera Statistics with R specialization

UAI 2015. Kernel-based just-in-time learning for expectation propagation

Probabilistic Programming with Gaussian processes in Julia

Dirichlet Process K-means

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

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

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

Topic modelling on financial news with Natural Language Processing

Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al

The Trendiness of Trends

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

Inferring Concept Prerequisite Relations from Online Educational Resources (IAAI-19)

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

Material for a Bayesian statistics workshop

Bayesian Evolutionary Analysis by Sampling Trees

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Expressions and dataframes with statistical details 📉 📜🔣✅

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

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

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

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:

High performance topic modeling for Ruby

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

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

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

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

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.

Tree Approximate Message Passing