probabilistic-graphical-models
There are 233 repositories under probabilistic-graphical-models topic.
kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
jmschrei/pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
guoguibing/librec
LibRec: A Leading Java Library for Recommender Systems, see
pgmpy/pgmpy
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
TuringLang/Turing.jl
Bayesian inference with probabilistic programming.
jaanli/variational-autoencoder
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
dotnet/mbmlbook
Sample code for the Model-Based Machine Learning book.
probcomp/PClean
A domain-specific probabilistic programming language for scalable Bayesian data cleaning
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.
biaslab/ForneyLab.jl
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
AliMorty/Markov-Random-Field-Project
This project has two parts. In part one, we use markov random field to denoise an image. In Part two, we use similar model for image segmentation.
ReactiveBayes/ReactiveMP.jl
High-performance reactive message-passing based Bayesian inference engine
florist-notes/CS228_PGM
🌀 Stanford CS 228 - Probabilistic Graphical Models
meringlab/FlashWeave.jl
Inference of microbial interaction networks from large-scale heterogeneous abundance data
kpoeppel/pytorch_probgraph
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
Novartis/scar
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
flyaflya/causact
causact: R package to accelerate computational Bayesian inference workflows in R through interactive visualization of models and their output.
ilabcode/pyhgf
PyHGF: A neural network library for predictive coding
diningphil/CGMM
Official Repository of "Contextual Graph Markov Model" (ICML 2018 - JMLR 2020)
stefanwebb/flowtorch-old
Separating Normalizing Flows code from Pyro and improving API
andreacasalino/Easy-Factor-Graph
General purpose C++ library for managing discrete factor graphs
xzluo97/MvMM-RegNet
Code for paper: MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation (MICCAI 2020)
UBC-Stat-ML/blangSDK
Blang's software development kit
deep-learning-drizzle/deep-learning-drizzle.github.io
webpage for maintaining the list of openly available DL, ML, RL, Vision, NLP, Optimization courses
agrumery/aGrUM
This repository is a mirror. If you want to raise an issue or contact us, we encourage you to do it on Gitlab (https://gitlab.com/agrumery/aGrUM).
sadrasabouri/pyrandwalk
:walking:Python Library for Random Walks
trungnt13/odin-ai
Orgainzed Digital Intelligent Network (O.D.I.N)
antoine-moulin/MVA
Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.
ml-uol/prosper
A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
hyu-ub/BayesNetBP
R package for inference in Bayesian networks.
ginevracoal/statistical-machine-learning
Probabilistic Machine Learning course lab @UNITS
xuedong/machine-learning-summer-schools
Curated materials for different machine learning related summer schools
xzluo97/MvMM-Demo
PyTorch implementation for multivariate mixture model on cardiac segmentation from multi-source images (TPAMI 2019)
chyikwei/bnp
Bayesian nonparametric models for python
samuelsonric/AlgebraicInference.jl
Bayesian inference on wiring diagrams.
tare/Splotch
Splotch is a hierarchical generative probabilistic model for analyzing Spatial Transcriptomics (ST) data