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Tensorflow implementation of Gated Graph Neural Network for Graph Classification
PyTorch implementation for Graph Gated Neural Network (for Knowledge Graphs)
Must-read papers on graph neural networks (GNN)
GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Also, GraMi supports user-defined structural and semantic constraints over the results, as well as approximate results. For more details, check our paper: Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB, 7(7):517-528, 2014.
links to conference publications in graph-based deep learning
Graph model implementation
Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net
All materials related tp GNN
GraphGallery is a gallery of state-of-the-art Graph Neural Networks (GNNs) for TensorFlow 2.x and PyTorch.
Hypergraph Algorithms Package
Network Embedding
Heterogeneous Information Network Datasets
Hypergraphs
Python package for hypergraph analysis and visualization.
ICLR 2022 Paper submission trend analysis from https://openreview.net/group?id=ICLR.cc/2022/Conference
【Java学习+面试指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。
Alternative to TensorFlow2/Keras/PyTorch for more concise, robust and optimized deep learning code
两只蠢萌京东的分布式爬虫.
A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"
KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.
code of HetGNN
LibKGE - A knowledge graph embedding library for reproducible research
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry Benchmark, ICLR 2019
A High Performance Library for Link Prediction in Complex Networks
small template code to create a multilayer network using matplotlib and networkx
Molecular Graph Convolutional Neural Networks
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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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.