logseminar / Schedule
Schedule for learning on graphs seminar
☆111Updated last year
Alternatives and similar repositories for Schedule:
Users that are interested in Schedule are comparing it to the libraries listed below
- Papers about out-of-distribution generalization on graphs.☆164Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆53Updated last year
- ☆57Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆79Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆76Updated 3 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆163Updated last year
- A paper collection about automated graph learning☆98Updated 8 months ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆84Updated 2 years ago
- ☆51Updated 2 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆107Updated last year
- ☆131Updated last year
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆238Updated 2 months ago
- Awesome literature on imbalanced learning on graphs☆75Updated 5 months ago
- A Survey of Learning from Graphs with Heterophily☆118Updated last month
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆87Updated 8 months ago
- Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github …☆53Updated 4 months ago
- The source code of HeCo☆159Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆77Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆191Updated 3 months ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆121Updated 11 months ago
- How Powerful are Spectral Graph Neural Networks☆70Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆27Updated last year
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆113Updated 2 years ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆61Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆120Updated 2 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆64Updated last year
- ☆104Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆110Updated 5 months ago