Alternatives and similar repositories for chainer-nri:

Users that are interested in chainer-nri are comparing it to the libraries listed below

• arthurmensch / online_sinkhorn
  ☆13Updated 4 years ago
• vsuriya93 / Deep-Learning-for-Graph-Representations
  This contains my M.Tech project work on using Deep Leanring for learning graph representations. Data will be provided on request
  ☆33Updated 7 years ago
• enalisnick / mixture_density_VAEs
  Variational Autoencoders with Gaussian Mixture Latent Space
  ☆36Updated 7 years ago
• Cyanogenoid / perm-optim
  [ICLR 2019] Learning Representations of Sets through Optimized Permutations
  ☆36Updated 5 years ago
• msobroza / SparsemaxPytorch
  SparseMax activation function implementation (ICML 2016) (PyTorch)
  ☆27Updated 7 years ago
• IuliaDuta / RSTG
  ☆39Updated 4 years ago
• MaestroGraph / sparse-hyper
  Code for the paper "Learning sparse transformations through backpropagation"
  ☆43Updated 5 years ago
• sungyubkim / amortized_svgd
  A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN
  ☆18Updated 6 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• AdamCobb / LCBNN
  ☆25Updated 2 years ago
• c-swm / c-swm
  This repository has moved to: https://github.com/tkipf/c-swm
  ☆27Updated 5 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆42Updated last year
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 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
• nzw0301 / pb-contrastive
  #UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning
  ☆12Updated 2 years ago
• imd-iclr / imd
  The Shape of Data: Intrinsic Distance for Comparing Data Distributions
  ☆12Updated 5 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• ermongroup / bgm
  Code for "Boosted Generative Models", AAAI 2018.
  ☆20Updated 7 years ago
• anirudh9119 / walkback_nips17
  Variational Walkback, NIPS'17
  ☆28Updated 7 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated last year
• melifluos / Hyperbolic-Embedding
  Learning neural network embeddings in hyperbolic spaces
  ☆14Updated 5 years ago
• sordonia / zforcing
  ZForcing Repo
  ☆40Updated 7 years ago
• LuisArmandoPerez / DiffusionVAE
  ☆29Updated 3 years ago
• graphreason / graphreason.github.io
  Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop)
  ☆26Updated 5 years ago
• d909b / ame
  🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…
  ☆41Updated last year
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• foxlf823 / DilatedRnn
  A PyTorch implement of Dilated RNN
  ☆11Updated 7 years ago
• gn-exp / gn-exp
  Anonymous Repository for ICML LRG Workshop: On Explainability Techniques for Graph Convolutional Networks
  ☆23Updated 5 years ago