uestclbh / PC-ConvLinks
☆14Updated last year
Alternatives and similar repositories for PC-Conv
Users that are interested in PC-Conv are comparing it to the libraries listed below
Sorting:
- A curated list of awesome graph structure learning approaches☆39Updated 8 months ago
- CIKM'23 - HoLe: Homophily-enhanced Structure Learning for Graph Clustering☆10Updated last year
- The code for "SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization"☆13Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆84Updated 8 months ago
- [NeurIPS'24] The source code for "Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning".☆28Updated 5 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 3 years ago
- [IJCAI'23] LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity☆17Updated 9 months ago
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆35Updated 3 months ago
- Code for GBK-GNN (paper accepted by WWW2022)☆16Updated 3 years ago
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆26Updated last year
- ☆38Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆42Updated 2 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- [NeurIPS 2024] State Space Models on Temporal Graphs: A First-Principles Study☆16Updated 7 months ago
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆37Updated last year
- ☆16Updated 2 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆46Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆55Updated last year
- [Neurips 2024] Disentangled Graph Homophily☆26Updated 6 months ago
- ☆19Updated 6 months ago
- A Survey of Learning from Graphs with Heterophily☆145Updated 5 months ago
- Official repository for NeurIPS 2023 paper "When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homo…☆21Updated 8 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
- 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
- A curated list of papers on graph transfer learning (GTL).☆17Updated last year
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆38Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆33Updated last year
- ☆18Updated 2 years ago