Alternatives and similar repositories for variational_dropout_sparsifies_dnn

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

• zihangdai / cegan_iclr2017
  Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"
  ☆24Updated 8 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 5 years ago
• rdevon / BGAN
  boundary-seeking generative adversarial networks
  ☆46Updated 8 years ago
• leonardblier / descriptionlengthdeeplearning
  Experiments from "The Description Length of Deep Learning Models"
  ☆10Updated 7 years ago
• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 7 years ago
• takerum / vat_chainer
  Implementation of Virtual adversarial training with chainer
  ☆40Updated 8 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 5 years ago
• moskomule / eve.pytorch
  ☆33Updated 4 years ago
• alykhantejani / nninit
  Weight initialization schemes for PyTorch nn.Modules
  ☆70Updated 8 years ago
• gngdb / variational-dropout
  Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.
  ☆33Updated 8 years ago
• bioinf-jku / coulomb_gan
  Implementation of Coulomb GANs
  ☆62Updated 4 years ago
• yaringal / acquisition_example
  Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function
  ☆16Updated 8 years ago
• paruby / Wasserstein-Auto-Encoders
  Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761
  ☆37Updated 7 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 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
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 6 years ago
• hal3 / macarico
  learning to search in pytorch
  ☆110Updated 5 years ago
• rarilurelo / pytorch_a3c
  ☆38Updated 8 years ago
• ml-lab / auxiliary-deep-generative-models
  Implementation of auxiliary deep generative models for semi-supervised learning
  ☆28Updated 10 years ago
• kefirski / bytenet
  Pytorch implementation of bytenet from "Neural Machine Translation in Linear Time" paper
  ☆46Updated 8 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆76Updated 5 years ago
• DLHacks / SRU
  The Statistical Recurrent Unit in Pytorch
  ☆34Updated 8 years ago
• leonardblier / alrao
  Implementation of "Learning with Random Learning Rates" in PyTorch.
  ☆102Updated 6 years ago
• tilarids / reinforcement_learning_playground
  Playground for reinforcement learning algorithms implemented in TensorFlow
  ☆16Updated 9 years ago
• ermongroup / Generalized-PixelVAE
  PixelVAE with or without regularization
  ☆68Updated 8 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• rachtsingh / lgamma
  Implementations of polygamma, lgamma, and beta functions for PyTorch
  ☆24Updated 8 years ago
• artix41 / AVO-pytorch
  Implementation of Adversarial Variational Optimization in PyTorch
  ☆43Updated 7 years ago
• jacobandreas / neuralese
  Translating neuralese
  ☆46Updated 8 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 9 years ago