cshjin / gnn_in_neurips_2019
A comprehensive collection of GNN works in NeurIPS 2019.
☆21Updated 4 years ago
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- Equivalence Between Structural Representations and Positional Node Embeddings☆21Updated 4 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆100Updated 4 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 4 years ago
- Code for Graphite iterative graph generation☆56Updated 5 years ago
- Learning Steady-States of Iterative Algorithms over Graphs☆39Updated 6 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆51Updated 4 years ago
- Implementation of SBM-meet-GNN☆22Updated 5 years ago
- Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop)☆26Updated 5 years ago
- Code for reproducing results in GraphMix paper☆71Updated last year
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- ☆44Updated 4 years ago
- ☆30Updated last year
- Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.☆53Updated 5 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 4 years ago
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆43Updated last year
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 6 years ago
- MATLAB implementation of linear support vector classification in hyperbolic space☆21Updated 6 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆36Updated 3 years ago
- Compute graph embeddings via Anonymous Walk Embeddings☆82Updated 6 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆40Updated 3 years ago
- Measuring and Improving the Use of Graph Information in Graph Neural Networks☆82Updated last month
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆23Updated 4 years ago
- TensorFlow implementation of Deep Graph Infomax☆63Updated 5 years ago
- ☆25Updated 5 years ago
- D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019☆125Updated 3 years ago
- Implicit Graph Neural Networks☆58Updated 2 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆91Updated 2 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆58Updated 3 years ago
- Variational Graph Convolutional Networks☆20Updated 3 years ago