LuckyGirl-XU / Awesome-DynamicGraphLearningLinks
☆34Updated last month
Alternatives and similar repositories for Awesome-DynamicGraphLearning
Users that are interested in Awesome-DynamicGraphLearning are comparing it to the libraries listed below
Sorting:
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆121Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆88Updated last year
- Advances on machine learning of graphs, covering the reading list of recent top academic conferences.☆232Updated 2 months ago
- A Library for Dynamic Graph Learning (NeurIPS 2023)☆287Updated 2 years ago
- [WWW 2024] Code and data for "On the Feasibility of Simple Transformer for Dynamic Graph Modeling"☆34Updated last year
- A Survey of Learning from Graphs with Heterophily☆157Updated 11 months ago
- ☆182Updated last year
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆64Updated 2 years ago
- [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.☆176Updated last week
- [Neurips 2024] Disentangled Graph Homophily☆28Updated last year
- "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023☆142Updated last year
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆270Updated last year
- ☆60Updated last year
- ☆104Updated 2 years ago
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆88Updated 8 months ago
- ☆137Updated 2 years ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆95Updated 8 months ago
- A curated list of papers on graph structure learning (GSL).☆53Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆123Updated 3 years ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆60Updated 2 years ago
- [WWW'24] Masked Graph Autoencoder with Non-discrete Bandwidths☆13Updated last year
- [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction☆54Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆58Updated 2 years ago
- ☆138Updated 2 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆47Updated last year
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆15Updated last year
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆117Updated 10 months ago
- Instant Graph Neural Networks for Dynamic Graphs☆11Updated 3 years ago
- A large-scale node-classification graph benchmark that brings together both the heterophily and heterogeneity properties of real-world gr…☆38Updated 6 months ago
- How Powerful are Spectral Graph Neural Networks☆75Updated 2 years ago