logseminar / ScheduleLinks
Schedule for learning on graphs seminar
☆109Updated last year
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.☆165Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆81Updated 4 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆170Updated last year
- Bag of Tricks for Graph Neural Networks.☆297Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆56Updated 2 years ago
- ☆135Updated 2 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- Awesome literature on imbalanced learning on graphs☆75Updated 10 months ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆64Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆84Updated 8 months ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 10 months ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆92Updated 2 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆104Updated last month
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆128Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- ☆139Updated last year
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 4 years ago
- Code of GAMLP for Open Graph Benchmark. KDD‘22☆62Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆200Updated 5 months ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- A paper collection about automated graph learning☆98Updated last year
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆65Updated last year
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆89Updated 3 years ago
- How Powerful are Spectral Graph Neural Networks☆73Updated 2 years ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆199Updated 7 months ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆33Updated last year
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- ☆55Updated 2 years ago