Deep Recurrent Graph Neural Network
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Updated
Nov 28, 2022 - Python
Deep Recurrent Graph Neural Network
Signed Whole Graph Embeddings
Streamlit App for Node and Graph Classification and Explainability
Project for the MVA course: Machine learning with kernel methods
Re-implementation of G-Mixup: Graph Data Augmentation for Graph Classification
repo for learning graph neural network
Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification (TKDE 2016)
The system effectively classifies different types of graphs using a CNN model, and writes short summary about graph in a clear and concise paragraph-like format.
Using StellarGraph to classify cell-pair interaction graphs from Giotto
Papers on Graph Pooling for GNN and their bioinformatics application
Zabbix Graphs Bottleneck Classification automates bottleneck analysis in network infrastructure using deep learning and the Zabbix monitoring system. It quickly identifies and classifies bottlenecks, enabling proactive network management and optimization.
NAGFS (Network Atlas-Guided Feature Selection) for a fast and accurate graph data classification code, recoded by Dogu Can ELCI.
This is the code of the paper Breaking the Expressive Bottleneck of Graph Neural Networks.
Graph registration network using representative templates
Implementation of Beltrami Flow & Neural Diffusion on Graphs (BLEND) by Chamberlain et al. (2021) for graph classification
Tangent Graph Neural Network
Tool to convert datasets from "Benchmark Data Sets for Graph Kernels" (K. Kersting et al., 2016) into a format suitable for deep learning research.
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