eugenium / LearnGraphDiscoveryLinks
Learnable Graph Discovery
☆10Updated 6 years ago
Alternatives and similar repositories for LearnGraphDiscovery
Users that are interested in LearnGraphDiscovery are comparing it to the libraries listed below
Sorting:
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 7 years ago
- PyTorch implementation of Stacked Capsule Auto-Encoders☆40Updated 11 months ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- ☆68Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 8 months ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆126Updated last year
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- Code for Graphite iterative graph generation☆59Updated 6 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 years ago
- ☆37Updated 6 years ago
- Black Box Variational Inference for Bayesian logistic regression☆18Updated 8 years ago
- D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019☆139Updated 4 years ago
- mean-field and structured VAEs for the IBP☆23Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for Sliced Gromov-Wasserstein☆68Updated 5 years ago
- A Python implementation of Kernel Mean Matching data reweighting algorithm☆32Updated 9 years ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- Collection of graph neural networks in pytorch☆50Updated 7 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- Implementation of a convolutional Variational-Autoencoder model in pytorch.☆74Updated 6 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆128Updated 5 years ago
- Path-SGD: Path-Normalized Optimization in Deep Neural Networks☆19Updated 6 years ago
- ☆63Updated 4 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆104Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago