Alternatives and similar repositories for MNIST-multitask:

Users that are interested in MNIST-multitask are comparing it to the libraries listed below

• shilpar27 / Label-embeddings-in-image-classification
  Convolutional Neural Networks (CNNs) are being widely used for various tasks in Computer Vision. We focus on the task of image classifica…
  ☆25Updated 7 years ago
• thuml / MTlearn
  Code release for "Learning Multiple Tasks with Multilinear Relationship Networks" (NIPS 2017)
  ☆71Updated 7 years ago
• zeakey / LDLForests
  Label Distribution Learning Forest
  ☆30Updated 7 years ago
• bruno-31 / GAN-manifold-regularization
  This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)
  ☆44Updated 5 years ago
• ToniCreswell / pyTorch_DAAE
  Demonising Adversarial Auto-encoder in PyTorch
  ☆24Updated 6 years ago
• cnichkawde / MatchingNetwork
  Implementation of "Matching Networks for One Shot Learning" in Keras https://arxiv.org/abs/1606.04080
  ☆54Updated 6 years ago
• FJR-Nancy / joint-cluster-cnn
  A tensorflow version of JULE (Joint Unsupervised Learning of Deep Representations and Image Clusters).
  ☆25Updated 6 years ago
• bruno-31 / gan-manifold-reg
  This is the code we used in our paper Manifold regularization with GANs for semi-supervised learning
  ☆24Updated 5 years ago
• chcorbi / MultiTaskLearning
  Package to apply MTL on a few dataset
  ☆26Updated 7 years ago
• mrottmann / DeepBASS
  Deep Bayesian Active Semi-Supervised Learning
  ☆11Updated 6 years ago
• CPJKU / deep_lda
  Implementation of Deep Linear Discriminant Analysis (DeepLDA)
  ☆48Updated 8 years ago
• zxlzr / Deep-Transfer-Learning
  Deep Transfer Learning Papers
  ☆78Updated 2 years ago
• shucunt / domain_adaptation
  this project is the code of domain adaptation referenced by unsupervised domain adaptation by backpropagation(http://machinelearning.wust…
  ☆63Updated 7 years ago
• MrGiovanni / Active-Learning
  [CVPR 2017] Official Implementation for AIFT
  ☆93Updated 3 years ago
• wOOL / DMTRL
  [Code] Deep Multi-task Representation Learning: A Tensor Factorisation Approach
  ☆58Updated 7 years ago
• michaal94 / Semisupervised-Clustering
  PyTorch semi-supervised clustering with Convolutional Autoencoders
  ☆24Updated 6 years ago
• seongjunyun / CNN-with-Dual-Local-and-Global-Attention
  Implementaion of Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction
  ☆121Updated 3 years ago
• animebing / mnist_tsne
  t-sne visualization of mnist images when feature is represented by raw pixels and cnn learned feature
  ☆63Updated 6 years ago
• wOOL / Learning_to_Compare
  Demo for the paper titled "Learning to Compare: Relation Network for Few-Shot Learning"
  ☆30Updated 7 years ago
• jindongwang / tf-dann
  Domain-Adversarial Neural Network in Tensorflow
  ☆37Updated 6 years ago
• xwcao / LowRankTRN
  Code for the paper "Tensor Regression Networks with various Low-Rank Tensor Approximations"
  ☆35Updated 6 years ago
• avijit9 / Contractive_Autoencoder_in_Pytorch
  Pytorch implementation of contractive autoencoder on MNIST dataset
  ☆53Updated 6 years ago
• ShadyF / cnn-rnn-classifier
  A practical example on how to combine both a CNN and a RNN to classify images.
  ☆53Updated 7 years ago
• markheimann / mSDA
  Implementation and usage of marginalized stacked denoising autoencoders (mSDA)
  ☆23Updated 8 years ago
• moskomule / pytorch.snapshot.ensembles
  PyTorch implementation of "SNAPSHOT ENSEMBLES: TRAIN 1, GET M FOR FREE" [WIP]
  ☆37Updated 7 years ago
• hiram64 / temporal-ensembling-semi-supervised
  Keras implementation of temporal ensembling(semi-supervised learning)
  ☆22Updated 6 years ago
• abhiskk / ladder
  Implementation of Ladder Network in PyTorch.
  ☆45Updated 7 years ago
• PAN001 / Deep-Neural-Network-Ensembles-for-Extreme-Classification
  Deep Neural Network Ensembles for Extreme Classification
  ☆42Updated 5 years ago
• zhuxinqimac / B-CNN
  Sample code of B-CNN paper (https://arxiv.org/abs/1709.09890) written in Python3+.
  ☆54Updated 3 years ago
• pedroherrerovidal / Semi-supervised_Learning_DL
  Semi-supervised strategies based on Deep Learning to extract structure from images and improve supervised classification tasks.
  ☆10Updated 4 years ago