• 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...