delta2323 / gnn-asymptotics
Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.
☆30Updated 4 years ago
Alternatives and similar repositories for gnn-asymptotics
Users that are interested in gnn-asymptotics are comparing it to the libraries listed below
Sorting:
- Variational Graph Convolutional Networks☆22Updated 4 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- ☆31Updated 2 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆35Updated 5 years ago
- ☆27Updated 3 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 4 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆36Updated 4 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆52Updated 5 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Source code for PairNorm (ICLR 2020)☆76Updated 5 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 3 years ago
- A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)☆16Updated 3 years ago
- Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)☆16Updated 4 years ago
- Measuring and Improving the Use of Graph Information in Graph Neural Networks☆82Updated 9 months ago
- ☆25Updated 3 years ago
- Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning☆20Updated 3 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 4 years ago
- ☆12Updated 3 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020☆34Updated 4 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆45Updated 4 years ago
- ☆45Updated 4 years ago
- ☆12Updated 5 years ago
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆58Updated 5 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆41Updated 3 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 years ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆42Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year