Graph-and-Geometric-Learning / HyBRiDLinks
Official implementation of paper "Learning High-Order Relationships of Brain Regions" [ICML 2024]
☆20Updated 4 months ago
Alternatives and similar repositories for HyBRiD
Users that are interested in HyBRiD are comparing it to the libraries listed below
Sorting:
- ☆56Updated 3 years ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- ☆30Updated last year
- Implementation codes for NeurIPS23 paper "Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts"☆12Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated 2 years ago
- code for kdd feasibiiity☆12Updated 2 years ago
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆46Updated last year
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆35Updated 5 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆24Updated last year
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆40Updated 2 years ago
- The implementation for DropMessage.☆37Updated 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆44Updated 2 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆88Updated 11 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- Code for GBK-GNN (paper accepted by WWW2022)☆16Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- A collection of graph foundation models including papers, codes, and datasets.☆112Updated 3 months ago
- Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effe…☆26Updated last year
- Directional diffusion models☆42Updated 11 months ago
- Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning☆19Updated last year
- Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs☆63Updated 11 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- A curated list of papers on graph transfer learning (GTL).☆17Updated last year
- Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models☆10Updated last month
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 10 months ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆92Updated 4 months ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago