Alternatives and similar repositories for sparse_attentive_backtracking_release:

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

• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 7 years ago
• sordonia / zforcing
  ZForcing Repo
  ☆40Updated 7 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 6 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated last year
• greentfrapp / cond-shift-neurons
  Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)
  ☆28Updated 6 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• anirudh9119 / LM_GANS
  Professor Forcing, NIPS'16
  ☆46Updated 7 years ago
• yandexdataschool / gumbel_lstm
  Experiments with binary LSTM using gumbel-sigmoid
  ☆30Updated 4 years ago
• paruby / DIP-VAE
  An implementation of DIP-VAE from the paper "Variational Inference of Disentangled Latent Concepts from Unlabelled Observations" by Kumar…
  ☆24Updated 6 years ago
• ischlag / TPR-RNN
  Code for the publication Learning to Reason with Third-Order Tensor Products.
  ☆40Updated 6 years ago
• pemami4911 / REBAR-pytorch
  Implementation of REBAR in PyTorch
  ☆17Updated 6 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆99Updated 4 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 8 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 5 years ago
• wlwkgus / GibbsNet
  Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch
  ☆57Updated 7 years ago
• rizar / systematic-generalization-sqoop
  Code for "Systematic Generalization: What Is Required and Can It Be Learned"
  ☆37Updated 5 years ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆41Updated 6 years ago
• leonardblier / descriptionlengthdeeplearning
  Experiments from "The Description Length of Deep Learning Models"
  ☆10Updated 6 years ago
• wlwkgus / NoisyNaturalGradient
  Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"
  ☆121Updated 6 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• enalisnick / mixture_density_VAEs
  Variational Autoencoders with Gaussian Mixture Latent Space
  ☆36Updated 7 years ago
• RemiLeblond / SeaRNN-open
  Open source implementation of SeaRNN (ICLR 2018, https://openreview.net/forum?id=HkUR_y-RZ)
  ☆48Updated 6 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• brendenlake / meta_seq2seq
  PyTorch code for meta seq2seq learning
  ☆43Updated 5 years ago
• kingofspace0wzz / wae-rnf-lm
  Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…
  ☆63Updated 4 years ago
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 2 years ago
• ravidziv / Information-bottleneck
  Python implementation of the infomration bottleneck method (tishby et al, 1999)
  ☆36Updated 7 years ago
• jmtomczak / vae_vpflows
  Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling
  ☆91Updated 7 years ago