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Spektral: Graph Neural Networks in TensorFlow 2 and Keras. ... The source code of the project is available on Github. Read the documentation here.

25.11.2020 · Graph Structure of Neural Networks This repository is the official PyTorch implementation of Graph Structure of Neural Networks, by Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie, ICML 2020. The repository is heavily built upon pycls, an image classification codebase built by FAIR. Introduction

We develop a data-efficient Graph Convolutional Network (GCN) algorithm PinSage, which combines efficient random walks and graph convolutions to generate ...

Description: Implementing a graph neural network model for predicting the topic of a paper given its citations.

19.02.2019 · Graph Neural Networks for Social Recommendation. In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph data. These advantages of GNNs provide great potential to advance social recommendation since data in social ...

Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed ...

Blog: Graph Classification: The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables. Blog ...

A graph neural network (GNN) is a class of neural networks for processing data represented by graph data structures. They were popularized by their use in supervised learning on properties of various molecules. Since their inception, several variants of the simple message passing neural network (MPNN) framework have been proposed.

A quite new and fast-evolving field in machine learning is graph neural nets. ... I will omit the usual PyTorch boilerplate code here we need in order to ...

02.05.2018 · Graph Neural Networks in TensorFlow and Keras with Spektral. 1 code implementation • 22 Jun 2020. In this paper we present Spektral, an open-source Python library for building graph neural networks with TensorFlow and the Keras application programming interface. Classification General Classification +3. 1,953.

Easy-to-use and unified API: All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). PyG is ...