tigerbunny2023 / PROSELinks
code for progressive gsl
☆12Updated this week
Alternatives and similar repositories for PROSE
Users that are interested in PROSE are comparing it to the libraries listed below
Sorting:
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆17Updated 2 years ago
- The source code of SpCo☆34Updated 2 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆46Updated 3 years ago
- ☆38Updated 4 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- A collection of papers on Graph Structural Learning (GSL)☆58Updated 2 years ago
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆13Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆88Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 3 years ago
- ☆47Updated 3 years ago
- ☆27Updated 3 years ago
- Awesome literature on imbalanced learning on graphs☆74Updated last year
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆38Updated 2 years ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆104Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆34Updated 3 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆37Updated 2 years ago
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆39Updated 8 months ago
- Tail-GNN: Tail-Node Graph Neural Networks☆34Updated 4 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- ☆19Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆41Updated 2 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆48Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago