• DeepLab

  • Referenced in 20 articles [sw15303]
  • combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling...
  • PMTK

  • Referenced in 181 articles [sw14689]
  • Kevin Murphy’s textbook Machine learning: a probabilistic perspective, but can also be used independently ... software framework encompassing machine learning, graphical models, and Bayesian statistics (hence the logo). (Some methods...
  • hglasso

  • Referenced in 10 articles [sw11202]
  • problem of learning a high-dimensional graphical model in which there ... general framework to three widely- used probabilistic graphical models: the Gaussian graphical model, the covariance...
  • Venture

  • Referenced in 9 articles [sw14670]
  • models and inference problems in Venture are specified via a Turing-complete, higher-order probabilistic ... implementation that build on ideas from probabilistic graphical models. First, we describe the stochastic procedure ... supports custom control flow, higher-order probabilistic procedures, partially exchangeable sequences and “likelihood-free” stochastic...
  • REBA

  • Referenced in 3 articles [sw29435]
  • complementary strengths of declarative programming and probabilistic graphical models to represent and reason with...
  • foxPSL

  • Referenced in 2 articles [sw13725]
  • usually by combining logical representations with probabilistic graphical models. PSL can be seen as both...
  • Belief

  • Referenced in 1 article [sw14242]
  • BELIEF: Graphical Belief Function Models and Graphical Probabilistic Models. BELIEF is a Common Lisp implementation ... Kong fusion and propagation algorithm for Graphical Belief Function Models ... Lauritzen and Spiegelhalter algorithm for Graphical Probabilistic Models. It includes code for manipulating graphical belief...
  • OpenMarkov

  • Referenced in 2 articles [sw14326]
  • OpenMarkov is a software tool for probabilistic graphical models (PGMs) developed by the Research Centre...
  • PyGModels

  • Referenced in 1 article [sw38510]
  • PyGModels: A Python package for exploring Probabilistic Graphical Models with Graph Theoretical Structures. Probabilistic Graphical...
  • FACTORIE

  • Referenced in 13 articles [sw08947]
  • Factorie: Probabilistic programming via imperatively defined factor graphs. Discriminatively trained undirected graphical models have...
  • Pgmpy

  • Referenced in 1 article [sw38511]
  • Pgmpy: Probabilistic graphical models using python...
  • stagedtrees

  • Referenced in 1 article [sw32870]
  • probability models. Staged event trees are probabilistic graphical models capable of representing asymmetric conditional independence...
  • pyGM

  • Referenced in 1 article [sw38512]
  • simple Python-based interface for defining probabilistic graphical models (Bayesian networks, factor graphs, etc.) over...
  • abn

  • Referenced in 1 article [sw31036]
  • network analysis is a form of probabilistic graphical models which derives from empirical data...
  • Pgm

  • Referenced in 1 article [sw38514]
  • Probabilistic graphical models in python. This code is intended mainly as proof of concept...
  • JSNice

  • Referenced in 1 article [sw37814]
  • from existing data and then uses this model to predict properties of new, unseen programs ... formulation enables us to leverage powerful probabilistic graphical models such as conditional random fields (CRFs...
  • simPATHy

  • Referenced in 1 article [sw23961]
  • approach is built upon probabilistic graphical models and is thus especially suited for testing topological...
  • tsBNgen

  • Referenced in 1 article [sw35076]
  • Bayesian networks are a type of probabilistic graphical model widely used to model the uncertainties...
  • ReactomeFIViz

  • Referenced in 1 article [sw25625]
  • types into a pathway context using probabilistic graphical models. We believe our app will give...
  • UGM

  • Referenced in 1 article [sw28257]
  • functions implementing various tasks in probabilistic undirected graphical models of discrete data with pairwise...