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gl-catmull-clark

A javascript implementation of the Catmull-Clark subdivision surface algorithm

glumpy

Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization

gluon-cv

Gluon CV Toolkit

gluon-nlp

NLP made easy

gmm

gnn_community

Implementation of the paper "Community Detection with Graph Neural Networks", by J. Bruna and L. Li

gnnpapers

Must-read papers on graph neural networks (GNN)

google_refexp_toolbox

The toolbox for the Google Refexp dataset proposed in this paper: http://arxiv.org/abs/1511.02283

gpclust

Clustering time series using Gaussian processes and Variational Bayes.

gpflow

Gaussian processes in tensorflow

gptoolbox

Matlab toolbox for Geometry Processing.

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

gpytorchopt

Work in progress repo for Bayesian Optimization using GPyTorch

grabcut

A MATLAB implementation of GrabCut (excluding border matting and user editing)

grabcut-1

A GUI program of GrabCut.

grammar_variational_autoencoder

pytorch implementation of grammar variational autoencoder

graph-based-image-classification

Implementation of Planar Graph Convolutional Networks in TensorFlow

graph-based-nn

Graph Convolutional Networks (GCNs)

graph-cnn

Implementation of https://arxiv.org/abs/1703.00792.

graph-cnn-in-3d-point-cloud-classification

Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)

graph-generation

GraphRNN: A Deep Generative Model for Graphs

graph-partition-neural-network-samples

Sample Code for Graph Partition Neural Networks

graph-representation-learning

Autoencoders for Link Prediction and Semi-Supervised Node Classification

graph2gauss

Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".

graph2seq

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

graph2vec_tf

This repository contains the "tensorflow" implementation of our paper "graph2vec: Learning distributed representations of graphs".

graphgan

Implementation of GraphGAN in tensorflow

graphilt

Graph filtering toolbox

graphnn

Training computational graph on top of structured data (string, graph, etc)

graphsage

Representation learning on large graphs using stochastic graph convolutions.