Alternatives and similar repositories for active_learning

Users that are interested in active_learning are comparing it to the libraries listed below

• peiyunh / mat-vae
  A MATLAB implementation of Auto-Encoding Variational Bayes
  ☆48Updated 8 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 4 years ago
• anhncs / Probabilistic-Graphical-Models
  Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
  ☆104Updated 12 years ago
• dustinstansbury / medal
  Matlab Environment for Deep Architecture Learning
  ☆109Updated 11 years ago
• jiayuzhou / MALSAR
  Multi-task learning via Structural Regularization
  ☆135Updated 4 years ago
• caglar / autoencoders
  Implementation of several different types of autoencoders
  ☆116Updated 3 years ago
• kyunghyuncho / deepmat
  Matlab Code for Restricted/Deep Boltzmann Machines and Autoencoders
  ☆191Updated 10 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• jmetzen / sparse-filtering
  Unsupervised feature learning based on sparse-filtering
  ☆55Updated 11 years ago
• ToniCreswell / DAAE_
  Denoising Adversairal Autoencoders
  ☆41Updated 8 years ago
• zi-w / GP-EST
  Bayesian optimization with the Gaussian process assumption
  ☆30Updated 9 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• zhegan27 / dpfa_icml2015
  The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"
  ☆19Updated 10 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆95Updated 8 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆67Updated 8 years ago
• lucastheis / deepbelief
  Code for training and evaluating restricted Boltzmann machines (RBMs) and deep belief networks (DBNs).
  ☆61Updated 14 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• saemundsson / semisupervised_vae
  Replication of Semi-Supervised Learning with Deep Generative Models
  ☆100Updated 9 years ago
• ispamm / Lynx-Toolbox
  Lynx Matlab Toolbox
  ☆23Updated 9 years ago
• rajarsheem / libsdae-autoencoder-tensorflow
  A simple Tensorflow based library for deep and/or denoising AutoEncoder.
  ☆150Updated 7 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 8 years ago
• wenli-vision / svmplus_matlab
  An implementation of SVM+
  ☆26Updated 9 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 8 years ago
• trigeorgis / Deep-Semi-NMF
  Theano-based implementation of Deep Semi-NMF.
  ☆121Updated 10 years ago
• ramarlina / DenoisingAutoEncoder
  Python implementation of Stacked Denoising Autoencoders for unsupervised learning of high level feature representation
  ☆150Updated 10 years ago
• melihkandemir / atldgp
  Asymmetric Transfer Learning with Deep Gaussian Processes
  ☆18Updated 10 years ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆204Updated 10 years ago
• piotrmirowski / Tutorial_AutoEncoders
  Tutorial code for Auto-Encoders, implementing Marc'Aurelio Ranzato's Sparse Encoding Symmetric Machine and testing it on the MNIST handwr…
  ☆36Updated 11 years ago
• jacobeisenstein / DPMM
  Dirichlet process mixture model code in Matlab. Sampling and variational.
  ☆71Updated 13 years ago
• nitromannitol / stochastic-quasi-newton
  modular implementation of new algorithm
  ☆13Updated 11 years ago