graph-convolutional-networks

Graph Neural Network Library for PyTorch

A collection of important graph embedding, classification and representation learning papers with implementations.

links to conference publications in graph-based deep learning

A distributed graph deep learning framework.

Graph Convolutional Networks for Text Classification. AAAI 2019

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

A list of recent papers about Graph Neural Network methods applied in NLP areas.

A pytorch adversarial library for attack and defense methods on images and graphs

Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry

A curated list of fraud detection papers using graph information or graph neural networks

Grakn Knowledge Graph Library (ML R&D)

The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks

Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)

The Pytorch implementation for "Semantic Graph Convolutional Networks for 3D Human Pose Regression" (CVPR 2019).

Graph convolutional neural network for multirelational link prediction

Code for CVPR'19 paper Linkage-based Face Clustering via GCN

Efficient Graph Neural Networks - a curated list of papers and projects

Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry Benchmark, ICLR 2019

A tensorflow implementation of Knowledge Graph Convolutional Networks

Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

ACL 2019: Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks