Alternatives and similar repositories for Imsat

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

• eelxpeng / UnsupervisedDeepLearning-Pytorch
  This repository tries to provide unsupervised deep learning models with Pytorch
  ☆90Updated 7 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• wlwkgus / DeepSpectralClustering
  Pytorch Implemention of paper "Deep Spectral Clustering Learning", the state of the art of the Deep Metric Learning Paper
  ☆93Updated 6 years ago
• neale / Adversarial-Autoencoder
  An adversarial autoencoder implementation in pytorch
  ☆84Updated 6 years ago
• moskomule / cca.pytorch
  CCAs for looking into DNNs
  ☆70Updated 5 years ago
• eleniTriantafillou / few_shot_mAP_public
  This repository contains the code for the paper "Few-Shot Learning Through an Information Retrieval Lens". Eleni Triantafillou, Richard Z…
  ☆25Updated 7 years ago
• akosiorek / stacked_capsule_autoencoders
  ☆81Updated 3 years ago
• rcalland / deep-INFOMAX
  Chainer implementation of deep-INFOMAX
  ☆34Updated 6 years ago
• xjtushujun / Meta-weight-net_class-imbalance
  NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).
  ☆34Updated 5 years ago
• kylehkhsu / cactus-maml
  Code for Unsupervised Learning via Meta-Learning.
  ☆121Updated 6 years ago
• paruby / Wasserstein-Auto-Encoders
  Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761
  ☆37Updated 7 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 years ago
• vithursant / VAE-Gumbel-Softmax
  An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…
  ☆72Updated 7 years ago
• haebeom-lee / maml
  MAML implementation (tensorflow)
  ☆15Updated 6 years ago
• abhiskk / ladder
  Implementation of Ladder Network in PyTorch.
  ☆45Updated 7 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• j-min / Dropouts
  PyTorch Implementations of Dropout Variants
  ☆87Updated 7 years ago
• eyounx / GANMM
  Mixture of Generative Adversarial Networks for Clustering
  ☆16Updated 7 years ago
• weihua916 / imsat
  Reproducing code for the paper "Learning Discrete Representations via Information Maximizing Self-Augmented Training"
  ☆80Updated 5 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• liyu95 / SupportNet
  SupportNet: solving catastrophic forgetting in class incremental learning with support data
  ☆34Updated 6 years ago
• kylehkhsu / cactus-protonets
  Code for Unsupervised Learning via Meta-Learning.
  ☆66Updated 4 years ago
• sungraepark / Adversarial-Dropout
  ☆32Updated 6 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 7 years ago
• snap-stanford / comet
  [ICLR 2021] Concept Learners for Few-Shot Learning
  ☆115Updated 2 years ago
• bobchennan / VAE_NBP
  Variational Auto-encoder with Non-parametric Bayesian Prior
  ☆43Updated 8 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• yookoon / VLAE
  Code for Variational Laplace Autoencoders
  ☆54Updated 2 years ago
• chenpf1025 / noisy_label_understanding_utilizing
  ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
  ☆91Updated 4 years ago
• fducau / AAE_pytorch
  ☆200Updated 8 years ago