ZhenyuYangMQ / Awesome-Graph-Level-Learning
Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph representation learning, graph regression and graph classification to join this project as contribut…
☆54Updated 6 months ago
Alternatives and similar repositories for Awesome-Graph-Level-Learning:
Users that are interested in Awesome-Graph-Level-Learning are comparing it to the libraries listed below
- Collection of papers relating data-driven higher-order graph/networks researches.☆69Updated 2 years ago
- Schedule for learning on graphs seminar☆109Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 9 months ago
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆113Updated 2 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆135Updated 2 years ago
- Awesome literature on imbalanced learning on graphs☆75Updated 6 months ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆189Updated 2 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆166Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆245Updated 3 months ago
- ☆48Updated 2 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆121Updated last year
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆96Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆75Updated 4 months ago
- Papers about out-of-distribution generalization on graphs.☆166Updated last year
- A Survey of Learning from Graphs with Heterophily☆128Updated last month
- ☆57Updated 2 years ago
- ☆107Updated last year
- A collection of resources on attention-based graph neural networks☆65Updated last year
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆88Updated 3 years ago
- Code & data for AAAI'23 Oral paper "Heterogeneous Graph Masked Autoencoders".☆58Updated 2 years ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆153Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆122Updated 2 years ago
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆67Updated 5 months ago
- ☆46Updated 2 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆192Updated last month
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆94Updated last year
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.