logseminar / ScheduleLinks
Schedule for learning on graphs seminar
☆109Updated 2 years ago
Alternatives and similar repositories for Schedule
Users that are interested in Schedule are comparing it to the libraries listed below
Sorting:
- Papers about out-of-distribution generalization on graphs.☆167Updated 2 years ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆57Updated 2 years ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆63Updated last year
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆114Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆120Updated 2 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆67Updated last year
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆81Updated 4 years ago
- ☆138Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆170Updated last year
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆92Updated 4 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 4 months ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆263Updated 10 months ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆207Updated 9 months ago
- Bag of Tricks for Graph Neural Networks.☆299Updated last year
- Awesome literature on imbalanced learning on graphs☆74Updated last year
- ☆138Updated 2 years ago
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆115Updated 6 months ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆202Updated 8 months ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆90Updated 3 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆130Updated last year
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 2 years ago
- ☆60Updated 3 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- The source code of HeCo☆168Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- Code of GAMLP for Open Graph Benchmark. KDD‘22☆63Updated 3 years ago