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Name: GNN
Type: Organization
Bio: Graph Neural Networks, Graph Theory
Location: ECUT
Name: GNN
Type: Organization
Bio: Graph Neural Networks, Graph Theory
Location: ECUT
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).
attention mechanism for graph classification, significant sub-graph mining, graph disstillation
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
An autoML framework & toolkit for machine learning on graphs.
AutoGL is a graph learning framework with automatic machine learning techniques, and the 6th solution for AutoGraph Challenge@KDD'20
The 2nd place solution for KDD Cup AutoGraph2020
A curated list of awesome architecture search resources
A collection of important graph embedding, classification and representation learning papers with implementations.
Collection of resources related with Graph Contrastive Learning.
A curated list of awesome graph representation learning.
A curated list of network embedding techniques.
A curated list for awesome self-supervised learning for graphs.
Repository for benchmarking graph neural networks
Repository for benchmarking graph neural networks
The tensorflow code of the paper"Dual-Graph Convolutional Network Based on Band Attention and Sparse Constraint for Hyperspectral Band Selection"
Contrastive Learning of Structured World Models
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
Graph Convolutional Neural Networks with Complex Rational Spectral Filters
Tensorflow Implementation of ChannelNets (NeurIPS 18)
Superpixel for CIFAR dataset
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
CogDL: An Extensive Research Toolkit for Graphs
Comparison of graph models: GCN, GAT and GGNN. We use these models to predict objects in the image using the context information provided by Knowledge Graphs
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.