There are 8 repositories under graphical-models topic.
DGMs for NLP. A roadmap.
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
Robopy is a python port for Robotics Toolbox in Matlab created by Peter Corke
Graphical language server platform for building web-based diagram editors
Scalable inference for a generative model of astronomical images
Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum
Factored inference for discrete-continuous smoothing and mapping.
pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models
Graphical modeling and code generation tool based on UML state machines
Kalman Variational Auto-Encoder
A toolbox for differentially private data generation
Deep Markov Models
A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization"
Scalable open-source software to run, develop, and benchmark causal discovery algorithms
[ICCV'21] Official PyTorch implementation for paper "Spatially Conditioned Graphs for Detecting Human–Object Interactions"
This repo contains the code for the paper Neural Factor Graph Models for Cross-lingual Morphological Tagging.
Web-based client framework of the graphical language server platform
Example diagram editors built with Eclipse GLSP
Tree-Structured, First- and Higher-Order Linear Chain, and Semi-Markov CRFs
Software for learning sparse Bayesian networks
Java-based server framework of the graphical language server platform
Graphical language server platform for building web-based diagram editors
General purpose C++ library for managing discrete factor graphs
Linear Gaussian Bayesian Networks - Inference, Parameter Learning and Representation. đź–§
Graph Representation Analysis for Connected Embeddings
Automatic probabilistic programming for scientific machine learning and dynamical models