Graph-COM / SPELinks
Official code for SPE
☆17Updated last year
Alternatives and similar repositories for SPE
Users that are interested in SPE are comparing it to the libraries listed below
Sorting:
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆99Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆91Updated 2 years ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆14Updated last year
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆163Updated 2 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆72Updated last year
- [VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.☆20Updated 9 months ago
- ☆57Updated 4 years ago
- ☆18Updated 3 years ago
- [ICML 2025] Generalization Principles for Inference over Text-Attributed Graphs with Large Language☆19Updated 6 months ago
- ☆43Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- Graph Positional and Structural Encoder☆54Updated last year
- ☆25Updated last year
- ☆133Updated 9 months ago
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆17Updated 2 years ago
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆128Updated 5 months ago
- [NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framewor…☆22Updated 7 months ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- ☆91Updated 2 years ago
- Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering☆13Updated 2 years ago
- ☆156Updated 4 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆82Updated 2 years ago
- ☆50Updated last year
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆24Updated 2 years ago
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆28Updated 3 years ago
- PyG re-implementation of Neural Bellman-Ford Networks (NeurIPS 2021)☆75Updated 3 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆50Updated last year
- EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling☆67Updated 7 months ago
- [KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"☆47Updated 10 months ago
- ☆42Updated 3 years ago