Alternatives and similar repositories for LearnGraphDiscovery

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

• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 7 months ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• bneyshabur / path-sgd
  Path-SGD: Path-Normalized Optimization in Deep Neural Networks
  ☆19Updated 6 years ago
• Gordonjo / versa
  Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"
  ☆69Updated 4 years ago
• jcatw / dcnn
  An implementation of Diffusion-Convolutional Neural Networks in Lasagne and Theano.
  ☆34Updated 8 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆22Updated 5 years ago
• cambridge-mlg / SPVAE
  Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)
  ☆12Updated 5 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• umutsimsekli / sgd_tail_index
  The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"
  ☆25Updated 5 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• horacepan / gnns
  Collection of graph neural networks in pytorch
  ☆50Updated 7 years ago
• sigvae / SIGraphVAE
  ☆25Updated 5 years ago
• alelab-upenn / graph-scattering-transforms
  Code for experimentation on graph scattering transforms
  ☆29Updated 5 years ago
• gear / gfnn
  Graph Filter Neural Network (ICPR'20)
  ☆48Updated 4 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆104Updated 5 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆124Updated last year
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• dfdazac / dgi
  TensorFlow implementation of Deep Graph Infomax
  ☆62Updated 6 years ago
• keyonvafa / logistic-reg-bbvi-blog
  Black Box Variational Inference for Bayesian logistic regression
  ☆18Updated 8 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆57Updated 6 years ago
• jliu / graph-normalizing-flows
  Code for Graph Normalizing Flows.
  ☆61Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 4 years ago
• VoVAllen / diffpool
  ☆37Updated 6 years ago