downeykking / graph-papersLinks
Graph Neural Network, Self-Supervised Learning, Contrastive Learning, RecSys, Transformer Papers Reading Notes.
☆38Updated 2 years ago
Alternatives and similar repositories for graph-papers
Users that are interested in graph-papers are comparing it to the libraries listed below
Sorting:
- Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Grap…☆142Updated 2 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 3 years ago
- A Survey of Learning from Graphs with Heterophily☆154Updated 9 months ago
- ☆124Updated 2 years ago
- [WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"☆182Updated last year
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆38Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- Awesome literature on imbalanced learning on graphs☆75Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆31Updated last year
- Reimplementation of AAAI21 paper "Beyond Low-frequency Information in Graph Convolutional Networks" based on PyTorch and PyTorch Geometri…☆24Updated 3 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 3 years ago
- ☆38Updated 4 years ago
- ☆49Updated 2 years ago
- An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted b…☆64Updated 2 years ago
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆117Updated 8 months ago
- Graph based Knowledge Distillation: A Survey☆68Updated 2 years ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆266Updated last year
- KDD'22☆64Updated 3 years ago
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆29Updated last year
- ☆34Updated 2 years ago
- Code & data for AAAI'23 Oral paper "Heterogeneous Graph Masked Autoencoders".☆66Updated 2 years ago
- The implementation for DropMessage.☆38Updated 2 years ago
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆63Updated 2 years ago
- ☆80Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- Advances on machine learning of graphs, covering the reading list of recent top academic conferences.☆228Updated last month
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆47Updated last year
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆91Updated last year
- A curated list of papers and code related to class-imbalanced learning on graphs (CILG).☆43Updated 11 months ago
- Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs☆66Updated last year