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graph-machine-learning

Graph Machine Learning, published by Packt

graph2vec

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

graph4nlp

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!

graph_attention_pool

Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)

graph_cnn

graph_convolutional_networks_node_classification

graph_convolutional_nn_molecule_maker

A Graph Neural Network (Geometric machine learning) for molecular generation

graph_nets

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

graph_weather

PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

graphgym

Platform for designing and evaluating Graph Neural Networks (GNN)

graphneuralnet

A simple Graph Net in PyTorch

graphsage

Representation learning on large graphs using stochastic graph convolutions.

graphsaint

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

graphsmote

Pytorch implementation of paper 'GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks' to appear on WSDM2021

graphtsne

PyTorch implementation of GraphTSNE, ICLR’19

grasp

GraSP: a Graph Signal Processing toolbox for Matlab

grokkinmachinelearning_luisserrano

Repository for the book Grokking Machine Learning, by Manning Editors

gsp-graph-learning

gsp-intro-grasp-code-book-ortega

Code for the GraSP appendix of the book "Introduction to Graph Signal Processing"

gspbox

Graph Signal Processing in Matlab

gtc2017-numba

Numba tutorial for GTC 2017 conference

guix

GNU Guix

hands-on-gnn-book

Hands-On Graph Neural Networks Using Python, published by Packt

hands-on-gpu-accelerated-computer-vision-with-opencv-and-cuda

Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt

hands-on-natural-language-processing-with-python

Hands On Natural Language Processing with Python, published by Packt

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

how_attentive_are_gats

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

hpc-ai-engineers-toolkit

HPC and Linux Toolbox

hpc-cheatsheets

Collection of cheat sheets

hpc-code-training-material

A collection of code examples as well as presentations for training purposes