Graph-and-Geometric-Learning / HyBRiD
Official implementation of paper "Learning High-Order Relationships of Brain Regions" [ICML 2024]
☆17Updated last month
Alternatives and similar repositories for HyBRiD:
Users that are interested in HyBRiD are comparing it to the libraries listed below
- Benchmarks for Graph Machine Learning in Brain Connectomics☆33Updated 2 months ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- A curated list of papers on graph transfer learning (GTL).☆17Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆42Updated last year
- Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models☆10Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆17Updated last year
- ☆52Updated 2 years ago
- Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effe…☆24Updated 9 months ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆21Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 10 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆29Updated last year
- A curated list of papers on graph structure learning (GSL).☆48Updated 3 months ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆42Updated 11 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [ICLR 2024] heterogeneous MoE: mixture of weak & strong experts on graphs https//openreview.net/pdf?id=wYvuY60SdD☆14Updated 2 weeks ago
- ☆18Updated 3 months ago
- Published papers focusing on graph domain adaptation, with survey paper online as Domain Adaptation for Graph Representation Learning: Ch…☆41Updated this week
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆80Updated 5 months ago
- NeurIPS 2022 paper, SubHypergraph Inductive Neural nEtwork☆17Updated last year
- Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning☆19Updated last year
- A pytorch implementation of H2GCN raised in the paper "Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Desig…☆35Updated 2 years ago
- ☆37Updated 3 years ago
- [KDD 2024] Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective☆15Updated 10 months ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆84Updated 5 months ago
- ☆16Updated last year
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆79Updated 2 years ago