Projects in Awesome Lists tagged with probabilistic-graphical-models

https://github.com/kmario23/deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

artificial-intelligence-algorithms artificial-neural-networks bayesian-statistics computer-vision deep-learning deep-neural-networks deep-reinforcement-learning explainable-ai geometric-deep-learning graph-neural-networks machine-learning medical-imaging natural-language-processing optimization pattern-recognition probabilistic-graphical-models probability reinforcement-learning speech-recognition visual-recognition

Last synced: 25 Mar 2025

https://github.com/jmschrei/pomegranate

Fast, flexible and easy to use probabilistic modelling in Python.

machine-learning probabilistic-graphical-models python pytorch

Last synced: 12 May 2025

https://github.com/guoguibing/librec

LibRec: A Leading Java Library for Recommender Systems, see

collaborative collaborative-filtering factorization filtering java matrix matrix-factorization probabilistic-graphical-models recommendation-algorithms recommender recommender-systems sparse systems tensor tensor-factorization

Last synced: 14 May 2025

https://github.com/turinglang/turing.jl

Bayesian inference with probabilistic programming.

artificial-intelligence bayesian-inference bayesian-neural-networks bayesian-statistics hamiltonian-monte-carlo hmc julia-language machine-learning mcmc probabilistic-graphical-models probabilistic-inference probabilistic-models probabilistic-programming turing

Last synced: 29 Apr 2026

https://github.com/TuringLang/Turing.jl

Bayesian inference with probabilistic programming.

artificial-intelligence bayesian-inference bayesian-neural-networks bayesian-statistics hacktoberfest hamiltonian-monte-carlo hmc julia-language machine-learning mcmc probabilistic-graphical-models probabilistic-inference probabilistic-models probabilistic-programming turing

Last synced: 15 Mar 2025

https://github.com/jaanli/variational-autoencoder

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

autoregressive-neural-networks deep deep-learning deep-neural-networks learning machine-learning probabilistic-graphical-models pytorch tensorflow unsupervised-learning vae variational-autoencoder variational-inference

Last synced: 08 Apr 2025

https://github.com/dotnet/mbmlbook

Sample code for the Model-Based Machine Learning book.

machine-learning probabilistic-graphical-models probabilistic-models probabilistic-programming

Last synced: 07 Apr 2025

https://github.com/probcomp/pclean

A domain-specific probabilistic programming language for scalable Bayesian data cleaning

bayesian-inference data-cleaning data-cleansing probabilistic-graphical-models probabilistic-programming

Last synced: 08 May 2025

https://github.com/probcomp/PClean

A domain-specific probabilistic programming language for scalable Bayesian data cleaning

bayesian-inference data-cleaning data-cleansing probabilistic-graphical-models probabilistic-programming

Last synced: 04 May 2025

https://github.com/hao-lh/the-books-making-you-better

A list of time-lasting classic books, which not only help you figure out how it works, but also grasp when it works and why it works in that way.

bayesian-inference computer-architecture computer-vision deep-learning high-performance-computing linear-algebra machine-learning probabilistic-graphical-models reinforcement-learning statistical-learning

Last synced: 15 Apr 2025

https://github.com/biaslab/forneylab.jl

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

bayesian-methods factor-graph machine-learning probabilistic-graphical-models probabilistic-programming state-space-models

Last synced: 06 Nov 2025

https://github.com/computationalpsychiatry/pyhgf

PyHGF: A neural network library for predictive coding

active-inference bayesian-filter bayesian-inference belief-propagation computational-psychiatry graph-neural-networks hierarchical-gaussian-filter jax neural-networks predictive-coding probabilistic-graphical-models reinforcement-learning state-space-model

Last synced: 12 Oct 2025

https://github.com/reactivebayes/reactivemp.jl

High-performance reactive message-passing based Bayesian inference engine

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: 12 Jul 2025

https://github.com/ReactiveBayes/ReactiveMP.jl

High-performance reactive message-passing based Bayesian inference engine

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: 04 May 2025

https://github.com/kpoeppel/pytorch_probgraph

A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch

deep-belief-network probabilistic-graphical-models pytorch restricted-boltzmann-machine

Last synced: 10 Mar 2026

https://github.com/flyaflya/causact

causact: R package to accelerate computational Bayesian inference workflows in R through interactive visualization of models and their output.

bayesian-inference dags posterior-probability probabilistic-graphical-models probabilistic-programming rstats-package

Last synced: 23 Feb 2026

https://github.com/novartis/scar

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

cite-seq crispr-screen denoising-algorithm generative-model machine-learning probabilistic-graphical-models pytorch single-cell-rna-seq variational-autoencoder

Last synced: 21 Jul 2025

https://github.com/Novartis/scar

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

cite-seq crispr-screen denoising-algorithm generative-model machine-learning probabilistic-graphical-models pytorch single-cell-rna-seq variational-autoencoder

Last synced: 28 Sep 2025

https://github.com/diningphil/CGMM

Official Repository of "Contextual Graph Markov Model" (ICML 2018 - JMLR 2020)

deep-learning graphs machine-learning probabilistic-graphical-models unsupervised-learning

Last synced: 27 Mar 2025

https://github.com/andreacasalino/easy-factor-graph

General purpose C++ library for managing discrete factor graphs

artificial-intelligence artificial-intelligence-algorithms bayesian-methods bayesian-network cpp factor-graph factor-graphs graphical-models machine-learning probabilistic-graphical-models probability training

Last synced: 04 Oct 2025

https://github.com/stefanwebb/flowtorch-old

Separating Normalizing Flows code from Pyro and improving API

bayesian-inference bayesian-statistics normalizing-flows probabilistic-graphical-models probabilistic-models probabilistic-programming pytorch

Last synced: 15 Jul 2025

https://gitlab.com/agrumery/aGrUM

aGrUM is a C++ library designed for easily building applications using graphical models such as Bayesian networks, influence diagrams, decision trees, GAI networks or Markov decision processes.

artificial-intelligence bayesian-network causal-inference causal-models causality cpp20 credal-network explainable-ai influence-diagram machine-learning-algorithms markov-network parallel-algorithm probabilistic-classifiers probabilistic-graphical-models probabilistic-models python python3 statistical-learning structural-learning

Last synced: 07 Oct 2025

https://github.com/trungnt13/odin-ai

Orgainzed Digital Intelligent Network (O.D.I.N)

bayesian-methods deep-learning deep-neural-networks disentangled-representations disentanglement-learning factor-vae generative-model graph-algorithms image-processing machine-learning natural-language-processing probabilistic-graphical-models probabilistic-programming semi-supervised-learning speech-processing text-processing variational-autoencoder variational-autoencoders

Last synced: 14 Mar 2026

https://github.com/sadrasabouri/pyrandwalk

:walking:Python Library for Random Walks

education educational markov-chain networkx probabilistic-graphical-models probability python random-walk reinforcement-learning reinforcement-learning-algorithms simulation stochastic-processes

Last synced: 16 Mar 2025

https://github.com/samuelsonric/algebraicinference.jl

Bayesian inference on wiring diagrams.

applied-category-theory bayesian-inference bayesian-statistics category-theory inference julia message-passing probabilistic-graphical-models

Last synced: 07 May 2025

https://github.com/chyikwei/bnp

Bayesian nonparametric models for python

bayesian data-analysis probabilistic-graphical-models python topic-modeling

Last synced: 03 May 2025

https://github.com/idsia/credici

Credici: Credal Inference for Causal Inference

causal-inference causal-models causality credal imprecise-probability probabilistic-graphical-models

Last synced: 09 Sep 2025

https://github.com/mpes-kit/fuller

Probabilistic machine learning for reconstruction and parametrization of electronic band sturcture from photoemission spectroscopy data

arpes band-structure electron-spectroscopy fitting inference machine-learning markov-random-field materials-informatics materials-science mpes photoemission probabilistic-graphical-models reconstruction

Last synced: 07 Apr 2026

https://github.com/cbg-ethz/sgs

Inference in Bayesian Networks with R

bayesian-network bayesian-networks graphical-models inference missing-data probabilistic-graphical-models

Last synced: 28 Apr 2025

https://github.com/tonysy/awesome-graph-networks

Materials for Graph Models and Graph Networks

artificial-intelligence deep-learning probabilistic-graphical-models

Last synced: 22 Jan 2026

https://github.com/idsia/crema

Crema: Credal Models Algorithms

bayesian bayesian-models credal credal-models crema imprecise-probability inference probabilistic-graphical-models probability

Last synced: 28 Apr 2025

https://github.com/aditeyabaral/lok-sabha-election-twitter-analysis

Twitter Feeds were analysed during the Lok Sabha Elections 2019 to guage the overall popularities of each party and predict the winner based solely on the tweets made by the population. This was made as a part of our Data Science course (UE18CS203) at PES University.

data-analysis data-science data-visualization elections loksabha nlp prediction probabilistic-graphical-models probability python python3 sentiment-analysis sentiment-classification sentiment-polarity sentiment-scores social-media socialmediaanalytics statistical-analysis statistical-models twitter

Last synced: 16 Apr 2025

https://github.com/ashwinpn/conditional-random-fields

An analysis and implementation of Conditional Random Fields.

conditional-random-fields crf data-science machine-learning nlp nlp-machine-learning pos-tagging probabilistic-graphical-models

Last synced: 13 Apr 2025

https://github.com/ekinakyurek/dpmm.jl

Clustering via Dirichlet Process Mixture Models

clustering dirichlet-process-mixtures probabilistic-graphical-models

Last synced: 11 Apr 2025

https://github.com/speedcell4/torchlatent

High Performance Structured Prediction in PyTorch

conditional-random-fields deep-learning latent-structures matrix-tree-theorem probabilistic-graphical-models pytorch

Last synced: 30 Sep 2025

https://github.com/doktormike/r-bayesian

This is the R Bayesian Data Science Toolkit

bayesian-applications bayesian-inference docker opencpu probabilistic-graphical-models probabilistic-programming

Last synced: 22 Apr 2025

https://github.com/iglesias/netpred

Structured learning with SVMs in C++ and Python

hidden-markov-model machine-learning network-science probabilistic-graphical-models support-vector-machines

Last synced: 05 Jan 2026

https://github.com/zeta611/stappl

🎲 Statically typed probabilistic programming language, feat. GADT

gadt generalized-algebraic-data-type ocaml probabilistic-graphical-models probabilistic-programming type-system

Last synced: 29 Jul 2025

https://github.com/anchen1011/image-segmentation-gibbs

Portable Image Segmentation with Gibbs'

gibbs-sampling image-segmentation probabilistic-graphical-models

Last synced: 10 Jan 2026

https://github.com/markdouthwaite/apogee

Bayesian Networks and Probabilistic Graphical Models for Python

artificial-intelligence bayesian-networks probabilistic-graphical-models probabilistic-programming

Last synced: 24 Mar 2025

https://github.com/vsimkus/pmr2024-pgm-demo

An official repository for a PGM demo of Probabilistic Modelling and Reasoning (2023/2024) - a University of Edinburgh master's course.

graphical-models probabilistic-graphical-models probabilistic-inference probability teaching

Last synced: 11 Apr 2025

https://github.com/ax-va/project-bayesianpy

This is a collection of algorithms and models written in Python for probabilistic programming. The main focus of the package is on Bayesian reasoning by using Bayesian networks, Markov networks, and their mixing.

bayesian-inference bayesian-machine-learning bayesian-network bayesian-networks bayesian-reasoning inference machine-learning machine-learning-algorithms markov-network markov-networks pgm probabilistic-graphical-models probabilistic-programming probabilistic-reasoning

Last synced: 31 Dec 2025

https://github.com/sidroopdaska/signlanguagerecogniser

hidden-markov-model model-selection probabilistic-graphical-models probabilistic-inference sign-language-recognition-system sign-language-recognizer statistical-models

Last synced: 27 Jan 2026

https://github.com/aarryasutar/pipe_leak_estimation_predictor_model

The project builds a Bayesian Network using pressure sensor data to detect pipe leaks, employing probabilistic reasoning to determine the likelihood of leaks based on sensor readings. It involves loading dataset, defining network structure, calculating CPDs, adding them to model, and using Variable Elimination algorithm for inference

bayesian-networks cpd csv dag data-frames inference model-verification numpy pandas pgmpy pressure-sensors probabilistic-graphical-models probability python variable-elimination-algorithm

Last synced: 15 Apr 2026

https://github.com/renatogeh/godrive

GoDrive is an application of autonomous driving through image classification using sum-product networks.

autonomous-driving gospn image-classification mobile-robots probabilistic-graphical-models spn sum-product-networks

Last synced: 14 May 2026

https://github.com/ashwinpn/ml-learnings

Concepts, Research Papers, Implementations - The works.

applied-mathematics artificial-intelligence convolutional-neural-networks graph-theory machine-learning machine-learning-algorithms neural-network probabilistic-graphical-models reinforcement-learning tutorial

Last synced: 09 Jun 2026

https://github.com/rwth-irt/bayesnet.jl

Type stable implementation of a Bayesian network.

julia-language probabilistic-graphical-models probabilistic-models probabilistic-programming

Last synced: 14 Mar 2025

https://github.com/jyuhuan/gossip

A Scala library for probabilistic graphical models.

probabilistic-graphical-models

Last synced: 12 Aug 2025

https://github.com/markdouthwaite/apogee-server

Probabilistic Graphical Models on Kubernetes

bayesian-networks gcp golang kuberenetes machine-learning probabilistic-graphical-models python skaffold tornado

Last synced: 19 May 2026

https://github.com/trungnt13/bay2-uef17

Bayesian Inference 2, University of Eastern Finland 2017

machine-learning probabilistic-graphical-models probabilistic-programming

Last synced: 28 Mar 2025

https://github.com/anchen1011/ros-robot-inference

Robot behavior inference system based on ROS

mcmc probabilistic-graphical-models python-client robot-inference ros

Last synced: 17 May 2026

https://github.com/aqib121201/interactive-bayesian-network-playground-with-inference-heatmaps

Visual web app to define & run inference on Bayesian networks with heatmap outputs

bayesian-networks belief-propagation inference pgmpy probabilistic-graphical-models visualization

Last synced: 18 Apr 2026

https://github.com/ilke-kas/probabilistic-graphic-models

A portfolio of advanced projects in probabilistic graphical models (PGMs), featuring hands-on notebooks for model design, inference, and real-world applications. Includes work on Bayesian networks, image denoising, and creative PGM explorations. Ideal for data science, machine learning, and AI.

ai bayesian-networks data-science inference machine-learning probabilistic-graphical-models python

Last synced: 09 May 2026

https://github.com/kavan-desai/probability-and-stochastic-process

Detailed Analysis of Probability and stochastic process with reference "Multiscale approach predictions for biological outcomes in ion-beam cancer therapy"

biology multiscale-approach prediction probabilistic-graphical-models probabilistic-programming probability python