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
  ☆66Updated 5 years ago
• moskomule / eve.pytorch
  ☆33Updated 4 years ago
• leonardblier / descriptionlengthdeeplearning
  Experiments from "The Description Length of Deep Learning Models"
  ☆10Updated 7 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 5 years ago
• tilarids / reinforcement_learning_playground
  Playground for reinforcement learning algorithms implemented in TensorFlow
  ☆16Updated 9 years ago
• RemiLeblond / SeaRNN-open
  Open source implementation of SeaRNN (ICLR 2018, https://openreview.net/forum?id=HkUR_y-RZ)
  ☆48Updated 7 years ago
• imatge-upc / danifojo-2018-repeatrnn
  Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
  ☆35Updated 7 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 5 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
• rarilurelo / pytorch_a3c
  ☆38Updated 8 years ago
• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 7 years ago
• bheinzerling / ran
  A PyTorch implementation of Recurrent Additive Networks by Lee et al. (2017)
  ☆29Updated 8 years ago
• bioinf-jku / coulomb_gan
  Implementation of Coulomb GANs
  ☆62Updated 4 years ago
• rdevon / BGAN
  boundary-seeking generative adversarial networks
  ☆46Updated 8 years ago
• ml-lab / auxiliary-deep-generative-models
  Implementation of auxiliary deep generative models for semi-supervised learning
  ☆28Updated 9 years ago
• dannysdeng / selu
  A pytorch implementation of "Self-Normalizing Neural Networks" by Klambauer et al. (still beta)
  ☆60Updated 8 years ago
• yaringal / acquisition_example
  Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function
  ☆16Updated 8 years ago
• hal3 / macarico
  learning to search in pytorch
  ☆110Updated 5 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• anirudh9119 / LM_GANS
  Professor Forcing, NIPS'16
  ☆45Updated 8 years ago
• takerum / vat_chainer
  Implementation of Virtual adversarial training with chainer
  ☆40Updated 8 years ago
• facebookresearch / noise-as-targets
  Unsupervised Learning by Predicting Noise
  ☆90Updated 4 years ago
• pfnet-research / chainer-ADDA
  Adversarial Discriminative Domain Adaptation in Chainer
  ☆24Updated 8 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆104Updated 9 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 9 years ago
• cjratcliff / variational-dropout
  TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)
  ☆16Updated 8 years ago
• DLHacks / SRU
  The Statistical Recurrent Unit in Pytorch
  ☆34Updated 8 years ago
• jmtomczak / vae_vpflows
  Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling
  ☆92Updated 8 years ago