Alternatives and similar repositories for Disentanglement_NEURIPS_2019

Users that are interested in Disentanglement_NEURIPS_2019 are comparing it to the libraries listed below

• haoliuhl / hybrid-discriminative-generative
  Hybrid Discriminative-Generative Training via Contrastive Learning
  ☆75Updated 2 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 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 7 years ago
• j-min / Dropouts
  PyTorch Implementations of Dropout Variants
  ☆88Updated 7 years ago
• HolyBayes / pytorch_ard
  Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
  ☆84Updated 4 years ago
• BorealisAI / bre-gan
  Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · …
  ☆20Updated 7 years ago
• Cyanogenoid / dspn
  [NeurIPS 2019] Deep Set Prediction Networks
  ☆101Updated 5 years ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆43Updated 6 years ago
• willwhitney / reprieve
  A library for evaluating representations.
  ☆77Updated 4 years ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆61Updated 3 years ago
• rdevon / cortex
  A machine learning library for PyTorch
  ☆94Updated 3 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 8 years ago
• yookoon / VLAE
  Code for Variational Laplace Autoencoders
  ☆54Updated 2 years ago
• dbaranchuk / memory-efficient-maml
  Memory efficient MAML using gradient checkpointing
  ☆86Updated 6 years ago
• cianeastwood / qedr
  Quantitative evaluation of disentangled representations
  ☆63Updated 7 years ago
• AIcrowd / neurips2019_disentanglement_challenge_starter_kit
  Starter Kit for the NeurIPS 2019 Disentanglement Challenge
  ☆33Updated 3 years ago
• david-abel / neurips_2019
  Notes from NeurIPS 2019
  ☆29Updated 6 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• facebookresearch / jacobian_regularizer
  A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.
  ☆129Updated 2 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 6 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 6 years ago
• ajayjain / lmconv
  Code for UAI 2020 paper "Locally Masked Convolution for Autoregressive Models"
  ☆79Updated 5 years ago
• fg91 / DeViSE-zero-shot-classification
  DeViSE model (zero-shot learning) trained on ImageNet and deployed on AWS using Docker
  ☆47Updated 6 years ago
• jlezama / disentangling-jacobian
  Source code for ICLR 2019 paper
  ☆24Updated 5 years ago
• lilianweng / generalization-experiment
  TBA
  ☆77Updated 6 years ago
• dfdazac / vaesbd
  Variational Autoencoder with Spatial Broadcast Decoder
  ☆35Updated 6 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆60Updated 6 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆193Updated 2 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago