rodrigo-pena / graph-learningLinks
☆14Updated 8 years ago
Alternatives and similar repositories for graph-learning
Users that are interested in graph-learning are comparing it to the libraries listed below
Sorting:
- ☆22Updated 4 years ago
- Gradient gating (ICLR 2023)☆55Updated 2 years ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated 2 years ago
- Scattering GCN: overcoming oversmoothness in graph convolutional networks☆25Updated 3 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- Topological Graph Neural Networks (ICLR 2022)☆124Updated 3 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 5 years ago
- ☆55Updated 3 years ago
- Python-based persistent homology algorithms☆19Updated 2 years ago
- GraphCON (ICML 2022)☆59Updated 3 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- A list for GNNs and related works.☆101Updated this week
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 3 years ago
- ☆17Updated 11 months ago
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆16Updated 2 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆86Updated last year
- ☆30Updated 4 years ago
- https://arxiv.org/abs/2005.06935☆12Updated 2 years ago
- Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.☆51Updated 8 months ago
- Graph signal processing tutorial, presented at the GraphSiP summer school.☆78Updated 6 years ago
- PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"☆48Updated last year
- Official repository for the Topological Deep Learning Challenge 2024, organized by TAG-DS & PyT-Team and hosted by GRaM Workshop @ ICML 2…☆40Updated 9 months ago
- PyTorch-Geometric Implementation of MarkovGNN method published in Graph Learning@WWW 2022 titled "MarkovGNN: Graph Neural Networks on Mar…☆13Updated 3 years ago
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆36Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Updated 5 years ago
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆44Updated 5 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- Generating PGM Explanation for GNN predictions☆76Updated 2 years ago
- Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)☆16Updated 5 years ago