• Scikit

  • Referenced in 630 articles [sw08058]
  • machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing...
  • Neural Network Toolbox

  • Referenced in 178 articles [sw07378]
  • dynamic networks. It also supports unsupervised learning with self-organizing maps and competitive layers. With...
  • KEEL

  • Referenced in 156 articles [sw06791]
  • various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based...
  • GloVe

  • Referenced in 100 articles [sw26211]
  • Word Representation. GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training...
  • DeepWalk

  • Referenced in 71 articles [sw39604]
  • present DeepWalk, a novel approach for learning latent representations of vertices in a network. These ... recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences...
  • STL-10 dataset

  • Referenced in 26 articles [sw39164]
  • image recognition dataset for developing unsupervised feature learning, deep learning, self-taught learning algorithms ... unlabeled examples is provided to learn image models prior to supervised training. The primary challenge ... challenging benchmark for developing more scalable unsupervised learning methods. Reference: Adam Coates, Honglak Lee, Andrew ... Analysis of Single Layer Networks in Unsupervised Feature Learning...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • been introduced within the context of statistical learning theory and structural risk minimization ... Fisher discriminant analysis and extensions to unsupervised learning, recurrent networks and control are available. Robustness...
  • StyleGAN

  • Referenced in 21 articles [sw42584]
  • architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • Statistics Toolbox™ provides statistical and machine learning algorithms and tools for organizing, analyzing, and modeling ... regression. The toolbox provides supervised and unsupervised machine learning algorithms, including support vector machines (SVMs...
  • mdp

  • Referenced in 11 articles [sw14129]
  • collection of supervised and unsupervised learning algorithms and other data processing units that...
  • CHIME

  • Referenced in 9 articles [sw28514]
  • with EM algorithm and its optimality. Unsupervised learning is an important problem in statistics...
  • VarNet

  • Referenced in 9 articles [sw42184]
  • propose a new model-based unsupervised learning method, called VarNet, for the solution of partial...
  • RolX

  • Referenced in 8 articles [sw32343]
  • linear in the number of edges), unsupervised learning approach for automatically extracting structural roles from...
  • RFCM

  • Referenced in 8 articles [sw02668]
  • rough and fuzzy sets. A hybrid unsupervised learning algorithm, termed as rough-fuzzy c-means...
  • InfoGAN

  • Referenced in 27 articles [sw40936]
  • that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN ... CelebA face dataset. Experiments show that InfoGAN learns interpretable representations that are competitive with representations...
  • quanteda

  • Referenced in 10 articles [sw30853]
  • applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses...
  • subgraph2vec

  • Referenced in 4 articles [sw36496]
  • neighbourhoods of nodes to learn their latent representations in an unsupervised fashion. We demonstrate that ... could be used for building a deep learning variant of Weisfeiler-Lehman graph kernel ... graph kernels on both supervised and unsupervised learning tasks. Specifically, on two realworld program analysis...
  • PixelVAE

  • Referenced in 4 articles [sw36214]
  • modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent...
  • 3DMatch

  • Referenced in 6 articles [sw32561]
  • present 3DMatch, a data-driven model that learns a local volumetric patch descriptor for establishing ... model, we propose an unsupervised feature learning method that leverages the millions of correspondence labels...
  • SOFAR

  • Referenced in 7 articles [sw31665]
  • with broad applications to both unsupervised and supervised learning tasks, such as biclustering with sparse...