probabilistic-graphical-models

There are 26 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!!
machine-learning deep-learning deep-neural-networks pattern-recognition computer-vision optimization visual-recognition reinforcement-learning deep-reinforcement-learning natural-language-processing artificial-neural-networks artificial-intelligence-algorithms probabilistic-graphical-models bayesian-statistics speech-recognition graph-neural-networks medical-imaging geometric-deep-learning explainable-ai probability
Language:HTML 11745
jmschrei / pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
machine-learning probabilistic-graphical-models python pytorch
Language:Python 3251
guoguibing / librec
LibRec: A Leading Java Library for Recommender Systems, see
recommender-systems recommendation-algorithms collaborative-filtering matrix-factorization tensor-factorization probabilistic-graphical-models recommender systems factorization matrix tensor collaborative filtering sparse java
Language:Java 3219
pgmpy / pgmpy
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
bayesian-networks causal-inference causal-models causality dag probabilistic-graphical-models python sampling-methods simulation statistical-inference statistics structure-learning
Language:Python 2612
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
Language:Julia 1963
jaanli / variational-autoencoder
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
vae machine-learning tensorflow variational-autoencoder variational-inference probabilistic-graphical-models deep learning deep-learning deep-neural-networks pytorch unsupervised-learning autoregressive-neural-networks
Language:Python 1116
dotnet / mbmlbook
Sample code for the Model-Based Machine Learning book.
machine-learning probabilistic-graphical-models probabilistic-models probabilistic-programming
Language:C# 278
probcomp / PClean
A domain-specific probabilistic programming language for scalable Bayesian data cleaning
probabilistic-programming probabilistic-graphical-models data-cleaning data-cleansing bayesian-inference
Language:Julia 214
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.
deep-learning machine-learning statistical-learning computer-vision linear-algebra bayesian-inference probabilistic-graphical-models computer-architecture reinforcement-learning high-performance-computing
169
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
Language:Julia 146
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.
image-segmentation probabilistic-graphical-models denoising-images markov-random-field
Language:Jupyter Notebook 110
ReactiveBayes / ReactiveMP.jl
High-performance reactive message-passing based Bayesian inference engine
bayesian-inference message-passing probabilistic-programming probabilistic-graphical-models inference julia variational-bayes variational-inference
Language:Julia 90
florist-notes / CS228_PGM
🌀 Stanford CS 228 - Probabilistic Graphical Models
cs228 probabilistic-graphical-models stanford-university markov-decision-processes bayesian
Language:Python 87
meringlab / FlashWeave.jl
Inference of microbial interaction networks from large-scale heterogeneous abundance data
metagenomics microbiome probabilistic-graphical-models high-performance-computing compositional-data metadata ecological-network co-occurence julia bioinformatics
Language:Julia 66
kpoeppel / pytorch_probgraph
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
probabilistic-graphical-models pytorch restricted-boltzmann-machine deep-belief-network
Language:Python 48
causact
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
Language:R 42
Novartis / scar
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
machine-learning single-cell-rna-seq denoising-algorithm variational-autoencoder probabilistic-graphical-models generative-model cite-seq crispr-screen pytorch
Language:Python 42
diningphil / CGMM
Official Repository of "Contextual Graph Markov Model" (ICML 2018 - JMLR 2020)
deep-learning probabilistic-graphical-models graphs unsupervised-learning machine-learning
Language:Python 36
stefanwebb / flowtorch-old
Separating Normalizing Flows code from Pyro and improving API
normalizing-flows pytorch bayesian-inference bayesian-statistics probabilistic-graphical-models probabilistic-programming probabilistic-models
Language:Python 36
ilabcode / pyhgf
PyHGF: A neural network library for predictive coding
bayesian-inference computational-psychiatry reinforcement-learning active-inference bayesian-filter predictive-coding hierarchical-gaussian-filter belief-propagation jax graph-neural-networks state-space-model neural-networks probabilistic-graphical-models
Language:Python 33
andreacasalino / Easy-Factor-Graph
General purpose C++ library for managing discrete factor graphs
bayesian-network cpp training machine-learning artificial-intelligence artificial-intelligence-algorithms bayesian-methods probabilistic-graphical-models probability factor-graph factor-graphs graphical-models
Language:C++ 28
xzluo97 / MvMM-RegNet
Code for paper: MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation
medical-image-registration groupwise-registration deep-learning tensorflow probabilistic-graphical-models
Language:Python 26
deep-learning-drizzle / deep-learning-drizzle.github.io
webpage for maintaining the list of openly available DL, ML, RL, Vision, NLP, Optimization courses
machine-learning deep-learning deep-neural-networks deep-reinforcement-learning computer-vision natural-language-processing machine-translation graph-neural-networks probabilistic-graphical-models medical-imaging speech-recognition
Language:HTML 23
UBC-Stat-ML / blangSDK
Blang's software development kit
machine-learning probabilistic-programming probabilistic-graphical-models probabilistic-models mcmc-sampler mcmc markov-chain-monte-carlo bayesian-inference bayesian-statistics
Language:Xtend 23
aGrUM
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).
bayesian-network influence-diagram markov-network probabilistic-graphical-models credal-network causal-inference causal-models causality probabilistic-inference probabilistic-classifiers python3 cpp20 parallel-algorithm artificial-intelligence explainable-ai python structural-learning xai machine-learning-algorithms statistical-learning
Language:Jupyter Notebook 21
trungnt13 / odin-ai
Orgainzed Digital Intelligent Network (O.D.I.N)
deep-learning deep-neural-networks speech-processing image-processing natural-language-processing text-processing probabilistic-programming probabilistic-graphical-models graph-algorithms bayesian-methods machine-learning variational-autoencoder variational-autoencoders factor-vae semi-supervised-learning disentangled-representations disentanglement-learning generative-model
Language:Python 21
ml-uol / prosper
A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
machine-learning sparse-coding feature-learning probabilistic-graphical-models variational-inference
Language:Python 20
antoine-moulin / MVA
Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.
convex-optimization graphs-classification object-recognition reinforcement-learning probabilistic-graphical-models deep-learning kernel-methods sequential-learning mva ens-paris-saclay
Language:Jupyter Notebook 19
pyrandwalk
sadrasabouri / pyrandwalk
:walking:Python Library for Random Walks
random-walk markov-chain stochastic-processes simulation probabilistic-graphical-models probability networkx reinforcement-learning reinforcement-learning-algorithms education educational python
Language:Jupyter Notebook 19
ginevracoal / statistical-machine-learning
Probabilistic Machine Learning course lab @UNITS
machine-learning tutorial probabilistic-programming probabilistic-graphical-models
Language:Jupyter Notebook 18
hyu-ub / BayesNetBP
R package for inference in Bayesian networks.
bayesian-networks network-inference probabilistic-graphical-models conditional-gaussian
Language:R 18
chyikwei / bnp
Bayesian nonparametric models for python
bayesian topic-modeling python data-analysis probabilistic-graphical-models
Language:Python 17
samuelsonric / AlgebraicInference.jl
Bayesian inference on wiring diagrams.
julia applied-category-theory category-theory bayesian-inference bayesian-statistics inference message-passing probabilistic-graphical-models
Language:Julia 17
tare / Splotch
Splotch is a hierarchical generative probabilistic model for analyzing Spatial Transcriptomics (ST) data
bioinformatics generative-model probabilistic-graphical-models spatial-transcriptomics
Language:R 17
xuedong / machine-learning-summer-schools
Curated materials for different machine learning related summer schools
machine-learning reinforcement-learning deep-learning statistics variational-inference optimization deep-reinforcement-learning optimal-transport automatic-differentiation probabilistic-graphical-models causal-inference generative-adversarial-network natural-language-processing kernel-methods multi-armed-bandits multi-agent gaussian-processes mcmc transfer-learning interpretability
Language:Jupyter Notebook 17
xzluo97 / MvMM-Demo
PyTorch implementation for multivariate mixture model on cardiac segmentation from multi-source images
combined-computing medical-image-segmentation medical-image-registration multivariate-mixture-model probabilistic-graphical-models pytorch
Language:Python 17