• GMRFLib

  • Referenced in 282 articles [sw06641]
  • Gaussian Markov random fields. Theory and applications. Researchers in spatial statistics and image analysis ... familiar with Gaussian Markov Random Fields (GMRFs), and they are traditionally among ... with such widespread use in the field of spatial statistics, it is surprising that there ... comprehensive reference on the subject.par Gaussian Markov Random Fields: Theory and Applications provides such...
  • QUIC

  • Referenced in 23 articles [sw11795]
  • underlying graph structure of a Gaussian Markov Random Field, from very limited samples. We propose...
  • ToulBar2

  • Referenced in 22 articles [sw07289]
  • Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction Problems, Weighted...
  • LibDAI

  • Referenced in 15 articles [sw06422]
  • networks) as well as undirected ones (Markov random fields and factor graphs). It offers various...
  • MALLET

  • Referenced in 22 articles [sw10602]
  • Markov Models, Maximum Entropy Markov Models, and Conditional Random Fields. These methods are implemented...
  • LatticeKrig

  • Referenced in 4 articles [sw15594]
  • package LatticeKrig: Multiresolution Kriging Based on Markov Random Fields. Methods for the interpolation of large ... compactly supported basis functions and a Markov random field model for the basis coefficients. These ... geometries besides a rectangular domain. The Markov random field approach combined with a basis function...
  • XMRF

  • Referenced in 4 articles [sw22303]
  • package XMRF: Markov Random Fields for High-Throughput Genetics Data. Fit Markov Networks...
  • foxPSL

  • Referenced in 2 articles [sw13725]
  • statistical relational learning, a recently developed field of machine learning that aims at representing both ... template language for hinge-loss Markov Random Fields, a type of continuous Markov Random fields...
  • glm-ie

  • Referenced in 2 articles [sw13249]
  • fully-connected undirected graphical models or Markov random fields with Gaussian and non-Gaussian potentials...
  • growfunctions

  • Referenced in 2 articles [sw16375]
  • Gaussian process (GP) or intrinsic Gaussian Markov random field (iGMRF) prior formulations where a Dirichlet...
  • HyPER

  • Referenced in 2 articles [sw23917]
  • graphical models known as hinge-loss Markov random fields. We experimentally evaluate our approach...
  • Characterness

  • Referenced in 2 articles [sw28333]
  • characters, we then design a Markov random field model so as to exploit the inherent...
  • BRISC

  • Referenced in 1 article [sw36600]
  • Haralick co-occurrence, Gabor filters, and Markov random fields. Gabor and Markov descriptors perform better...
  • LoMRF

  • Referenced in 1 article [sw35053]
  • LoMRF: Logical Markov Random Fields. LoMRF is an open-source implementation of Markov Logic Networks...
  • gamlss.spatial

  • Referenced in 1 article [sw36345]
  • allows us to fit Gaussian Markov Random Field within the Generalized Additive Models for Location...
  • SpaCEM3

  • Referenced in 1 article [sw20896]
  • algorithm for soft clustering and Markov Random Fields (MRF) for spatial modelling. The learning...
  • UGM

  • Referenced in 1 article [sw28257]
  • potentials. The last task focuses on Markov random fields and conditional random fields with...
  • MRF-MBNN

  • Referenced in 1 article [sw02098]
  • knowledge. This is achieved by including Markov random field (MRF) into the MBNN and this...
  • Conrad

  • Referenced in 1 article [sw23028]
  • gene predictor based on semi-Markov conditional random fields (SMCRFs). Unlike the best standalone gene ... predictors, which are based on generalized hidden Markov models (GHMMs) and trained by maximum likelihood...
  • smerfs

  • Referenced in 6 articles [sw23987]
  • efficient simulation of isotropic Gaussian random fields on the unit sphere is a task encountered ... numerical applications. A fast algorithm based on Markov properties and fast Fourier transforms...