• GraRep

  • Referenced in 9 articles [sw32342]
  • GraRep: Learning Graph Representations with Global Structural Information. In this paper, we present GraRep ... vertex representations of weighted graphs. This model learns low dimensional vectors to represent vertices appearing ... work, integrates global structural information of the graph into the learning process. We also formally...
  • SAP2000

  • Referenced in 24 articles [sw17041]
  • create structural models rapidly and intuitively without long learning curve delays. Now you can harness...
  • Rseslib

  • Referenced in 14 articles [sw30225]
  • rough set and machine learning algorithms and data structures in Java. It provides algorithms...
  • bnstruct

  • Referenced in 3 articles [sw29260]
  • package bnstruct: Bayesian Network Structure Learning from Data with Missing Values. Bayesian Network Structure Learning ... Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu...
  • RCV1

  • Referenced in 114 articles [sw07279]
  • benchmark several widely used supervised learning methods on RCV1-v2, illustrating the collection’s properties ... versions of the category assignments and taxonomy structures, via online appendices...
  • struc2vec

  • Referenced in 5 articles [sw36495]
  • struc2vec: Learning Node Representations from Structural Identity. Structural identity is a concept of symmetry ... structure and their relationship to other nodes. Structural identity has been studied in theory ... flexible framework for learning latent representations for the structural identity of nodes. struc2vec uses ... techniques for learning node representations fail in capturing stronger notions of structural identity, while struc2vec...
  • AIS-BN

  • Referenced in 25 articles [sw02223]
  • integrals and the structural advantages of Bayesian networks, (2) a smooth learning method...
  • pystruct

  • Referenced in 4 articles [sw14411]
  • Pystruct-learning structured prediction in Python. Structured prediction methods have become a central tool ... many machine learning applications. While more and more algorithms are developed, only very few implementations ... providing a general purpose implementation of standard structured prediction methods, both for practitioners...
  • BAYES-NEAREST

  • Referenced in 4 articles [sw02847]
  • data by using the K2 structural learning algorithm. The Nearest Neighbor algorithm is used...
  • PREvaIL

  • Referenced in 10 articles [sw25073]
  • residues using sequence, structural, and network features in a machine-learning framework. Determining the catalytic ... understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel ... including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive ... performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive...
  • MizarMode

  • Referenced in 18 articles [sw01973]
  • articles and abstracts, structured viewing, proof advice using trained machine learning tools like the Mizar...
  • PROFEAT

  • Referenced in 14 articles [sw16924]
  • statistical learning models for predicting proteins and peptides of different structural, functional and interaction profiles...
  • DirectLiNGAM

  • Referenced in 14 articles [sw15504]
  • Direct Method for Learning a Linear Non-Gaussian Structural Equation Model. Structural equation models...
  • CTBN-RLE

  • Referenced in 5 articles [sw12961]
  • learning, CTBN-RLE implements structure and parameter learning for both complete and partial data...
  • graph2vec

  • Referenced in 5 articles [sw32340]
  • Graphs. Recent works on representation learning for graph structured data predominantly focus on learning distributed...
  • MCL

  • Referenced in 7 articles [sw07231]
  • language is simple to learn and its structure is similar to Fortran. We report...
  • Prodigy

  • Referenced in 37 articles [sw20686]
  • basis for research in planning, machine learning, apprentice-type knowledge-refinement interfaces, and expert systems ... descriptions of the PRODIGY representation language, control structure, user interface, abstraction module, and other features ... basic features, as well as gradually learning the more esoteric aspects of PRODIGY4.0...
  • PcGive

  • Referenced in 50 articles [sw04927]
  • Professionaltm aims to give an operational and structured approach to econometric modelling using the most ... textbooks’ and `computer manuals’ by linking the learning of econometric methods and concepts...
  • lsl

  • Referenced in 2 articles [sw22965]
  • package lsl: Latent Structure Learning. Fits structural equation modeling via penalized likelihood...
  • Daikon

  • Referenced in 43 articles [sw04319]
  • executions. Dynamic invariant detection is a machine learning technique that can be applied to arbitrary ... Java, and Perl programs, and in record-structured data sources; it is easy to extend...