FilippoMB / Simplifying-Clustering-with-Graph-Neural-NetworksLinks
Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".
☆37Updated 5 months ago
Alternatives and similar repositories for Simplifying-Clustering-with-Graph-Neural-Networks
Users that are interested in Simplifying-Clustering-with-Graph-Neural-Networks are comparing it to the libraries listed below
Sorting:
- Generating PGM Explanation for GNN predictions☆75Updated 2 years ago
- ☆55Updated 3 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆46Updated last year
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆82Updated 2 years ago
- A list for GNNs and related works.☆99Updated 3 months ago
- Pytorch implementation of various Graph Neural Networks (GNNs) for graph classification☆112Updated 5 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆169Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆53Updated 2 years ago
- Dynamic Graph Benchmark☆82Updated 2 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆90Updated last year
- Parameterized Explainer for Graph Neural Network☆139Updated last year
- Code for our paper "Attending to Graph Transformers"☆90Updated last year
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 3 years ago
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆165Updated last year
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆159Updated last year
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆44Updated 2 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆68Updated 3 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- The official implementation of the Graph Barlow Twins method with the experimental pipeline☆31Updated last year
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- code implementation of SEP(ICML 2022)☆34Updated 3 years ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆166Updated 2 years ago
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆41Updated 2 years ago
- ☆55Updated last month
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆48Updated last year
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆24Updated 3 months ago
- [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction☆50Updated 10 months ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- Temporal Graph Benchmark project repo☆236Updated this week
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆42Updated 5 years ago