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awesome-graph-classification ... links to conference publications in graph-based deep learning ... Repository for benchmarking graph neural networks.

Awesome Graph Attack Papers is an open source software project. Adversarial attacks and defenses on Graph Neural Networks..

Sep 16, 2020 · Graph neural network, as a powerful graph representation learning method, has been widely used in diverse scenarios, such as NLP, CV, and recommender systems. As far as I can see, graph mining is highly related to recommender systems. Recommend one item to one user actually is the link prediction on the user-item graph.

Graph Based Deep Learning Literature ⭐ 3,440. links to conference publications in graph-based deep learning. Euler ⭐ 2,246. A distributed graph deep learning framework. Stellargraph ⭐ 2,227. StellarGraph - Machine Learning on Graphs. Spektral ⭐ 1,941. Graph Neural Networks with Keras and Tensorflow 2.

Paper Lists for Graph Neural Networks. Contribute to GRAND-Lab/Awesome-Graph-Neural-Networks development by creating an account on GitHub.

... part-1, part-2, part-3 AAAI 20: Graph Neural Networks: Models and ... A curated list for awesome graph representation learning resources ...

Paper Lists for Graph Neural Networks. Contribute to GRAND-Lab/Awesome-Graph-Neural-Networks development by creating an account on GitHub.

graph-neural-networks,Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting ...

Browse The Most Popular 3 Awesome Graph Neural Networks Open Source Projects

Graph Neural Networks (GNNs) are a class of deep learning methods designed to perform inference on data described by graphs. GNNs are neural ...

He and H. Zhao, "Fault Diagnosis and Location based on Graph Neural Network in Telecom Networks," 2020 International Conference on Networking and Network Applications (NaNA), Haikou City, China, 2020, pp. 304-309. doi: 10.1109/NaNA51271.2020.00059 Abstract: As the scale of telecom networks continues to expand and the structure becomes more ...

Python. A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019). A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019). A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

Dec 20, 2020 · Gaan: Gated attention networks for learning on large and spatiotemporal graphs. Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung. 2018. paper. Geniepath: Graph neural networks with adaptive receptive paths. Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi.

An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources. Jraph ⭐ 781 · A Graph Neural Network Library in Jax.

Paper Lists for Graph Neural Networks. Contribute to admdev8/Awesome-Graph-Neural-Networks development by creating an account on GitHub.

Efficient and Scalable GNN Architectures

Blog: Awesome Resources on Graph Neural Networks by Zonghan Wu. This is a collection of resources related with graph neural networks. Blog: Deep Learning on ...

Paper Lists for Graph Neural Networks. Contribute to RezaFeng/Awesome-Graph-Neural-Networks development by creating an account on GitHub.

Aug 11, 2021 · GNN-RecSys. This project was presented in a 40min talk + Q&A available on Youtube and in a Medium blog post. Graph Neural Networks for Recommender Systems. This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library. ( DGL ).