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app

The code of APP, Scalable Graph Embedding for Asymmetric Proximity. Zhou, Chang and Liu, Yuqiong and Liu, Xiaofei and Liu, Zhongyi and Gao, Jun AAAI 2017

d2age

The source codes for D2AGE model. Distance-aware DAG Embedding for Proximity Search on Heterogeneous Graphs.

deepwalk

DeepWalk - Deep Learning for Graphs

deepwalk-1

weighted deepwalk implementation in c++

differential_privacy

QGIS differential privacy processing plugin

differentially-private-sgd-1

directed_cell

Implementation of generative models for directed and weighted graphs using low-rank approximations

dp-gan

Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data

dpdpca

Codes for differentially-private distributed PCA

dpgan

Source code of paper "Differentially Private Generative Adversarial Network"

dpgan-2

Implementation of a differentially private generative adversarial network.

dpsgd-optimizer

Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enforces privacy by clipping and sanitising the gradients with Gaussian noise during training.

generative_adversarial_networks_pytorch

Implementations about GAN, Improved GAN, DCGAN, LAPGAN, and InfoGAN in PyTorch

graph-embedding

Four network embedding algorithms(deepwalk, node2vec, TADW ,LINE) for two datasets(Cora, Tencent Weibo)

graph-learning

graph_embeddings

Node2vec-DeepWalk-LINE algorithms for small, medium and large Datasets

graph_sampling

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

graphgan

A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)

graphsgan

Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data.

kernelkmeansnystrom

Kernel K-Means Sampling for Nystrom Approximation

link-prediction

Link prediction based on node2vec

link-prediction_with_deep-learning

link_prediction

netgan

Implementation of the paper "NetGAN: Generating Graphs via Random Walks".

netgan-1

network-representation-learning

network-representation-learning: DeepWalk, LINE, Node2Vec, GraRep

node2vec

node2vec_linkprediction

Testing link prediction using Node2Vec with AUC test

ppgans-privacy-preserving-gans

PPGANs: Privacy-preserving Generative Adversarial Networks。

privpfc

Differentially private data publishing algorithm for classification