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adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

adversarialnetspapers

The classical paper list with code about generative adversarial nets

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

arga

This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, [https://www.ijcai.org/proceedings/2018/0362.pdf].

authorship-attribution

awesome-network-embedding

A curated list of network embedding techniques.

bert

TensorFlow code and pre-trained models for BERT

bert-related-papers

BERT-related papers

bjutthesis

LaTeX-based Template for thesis of Beijing University of Technology(BJUT)

data-mining-conferences

Ranking, acceptance rate, deadline, and publication tips

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deeplearning

深度学习入门教程&&优秀文章&&Deep Learning Tutorial

ganhacks

starter from "How to Train a GAN?" at NIPS2016

gat

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

gcn

changing GCN

gnnpapers

Must-read papers on graph neural networks (GNN)

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

graphgan

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

han

Network Embedding

hegan

Source code for KDD 2019 paper "Adversarial Learning on Heterogeneous Information Networks"

hin-datasets-for-recommendation-and-network-embedding

Heterogeneous Information Network Datasets for Recommendation and Network Embedding

hin2vec

Heterogeneous information network representation learning

keras-bert

Implementation of BERT that could load official pre-trained models for feature extraction and prediction

lgcn

Tensorflow Implementation of Large-Scale Learnable Graph Convolutional Networks (LGCN) KDD18

linearfw

Frank-Wolfe optimization variants with a linear convergence rate

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

machinelearning

Machine learning resources

machinelearning_python

机器学习算法python实现

meta-learning-papers

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

nrlpapers

Must-read papers on network representation learning (NRL) / network embedding (NE)