A Collection of Utilities for Modeling Multivariate Data Using Probabilistic Graphical Models
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Updated
Nov 6, 2017 - C++
A Collection of Utilities for Modeling Multivariate Data Using Probabilistic Graphical Models
Realistic simulation of property graphs
General purpose C++ library for managing discrete factor graphs
Probabilistic inference of somatic copy number alterations using repeat DNA (FAST-SeqS)
Repo to build Bayesian Networks in c++
Implemented a Bayesian network for Optical Character Recognition. Implemented inference algorithmic techniques i.e. message passing and loop belief propagation
(Reproduction)Sum-product network implementation and its application to image completion.
An ASCII visualizer for the probability mass function of a binomial distribution.
Implemented the Gibbs sampler over the Markov network structure to perform inference over the OCR graphical models.
Cutset networks implementation in C++
Implementation of the an algorithm that finds conditional in-dependencies between different nodes in the network.
Discrete factor operations for probabilistic graphical models
Text language detector based on n-grams
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