• PMTK

  • Referenced in 153 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...
  • DeepLab

  • Referenced in 13 articles [sw15303]
  • combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling...
  • hglasso

  • Referenced in 9 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 8 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...
  • 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...
  • REBA

  • Referenced in 2 articles [sw29435]
  • complementary strengths of declarative programming and probabilistic graphical models to represent and reason with...
  • OpenMarkov

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

  • Referenced in 12 articles [sw08947]
  • Factorie: Probabilistic programming via imperatively defined factor graphs. Discriminatively trained undirected graphical models have...
  • stagedtrees

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

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

  • Referenced in 4 articles [sw29880]
  • user to specify probabilistic models in the form of graphical models, Bayesian networks, or factor...
  • UGM

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

  • Referenced in 0 articles [sw33101]
  • computer vision, machine learning, and probabilistic graphical models. The code is maintained by me (Stephen...
  • GPU-PRISM

  • Referenced in 2 articles [sw19543]
  • graphics processing units (GPUs). The extension is based on parallel algorithms for probabilistic model checking...
  • DiPro

  • Referenced in 4 articles [sw09744]
  • MRMC probabilistic model checkers. It allows for the computation of probabilistic counterexamples for discrete time ... MDPs). The computed counterexamples can be rendered graphically...
  • HMMER

  • Referenced in 17 articles [sw10514]
  • suite for protein sequence similarity searches using probabilistic methods. Previously, HMMER has mainly been available ... feasible to make efficient profile hidden Markov model (profile HMM) searches ... number of matches found, developing graphical summaries of the search results to provide quick, intuitive...