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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Updated
Feb 6, 2020 - Python
Tool to convert datasets from "Benchmark Data Sets for Graph Kernels" (K. Kersting et al., 2016) into a format suitable for deep learning research.
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations [AAAI-2020]
One-representative shot learning for graph classification.
Signed Whole Graph Embeddings
A repo for baseline of graph pooling.
repo for learning graph neural network
Software implementation of Pyramidal Reservoir Graph Neural Networks
Pattern Mining for the Classification of Public Procurement Fraud
Few-Shot Graph Classification via distance metric learning.
Project for the MVA course: Machine learning with kernel methods
This is the code of the paper Breaking the Expressive Bottleneck of Graph Neural Networks.
Project for Deep Learning And Applied AI course at the University of "La Sapienza" in Master in Computer Science A.A. 2021/2022
Implementation of Beltrami Flow & Neural Diffusion on Graphs (BLEND) by Chamberlain et al. (2021) for graph classification
Tangent Graph Neural Network
Deep Recurrent Graph Neural Network
HADA (Hiearachical Adversarial Domain Alignment) for brain graph prediction and classification.
Unified multimodal classifier: a unified brain graph classification model trained on unpaired multimodal brain graphs, which can classify any brain graph of any size.
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