2015lab1

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].

cf-nade

A implementation of CF-NADE. Yin Zheng, et. al. "A Neural Autoregressive Approach to Collaborative Filtering", accepted by ICML 2016.

gcmc

Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction

gcn

Implementation of Graph Convolutional Networks in TensorFlow

graphexp

Interactive visualization of the Gremlin graph database with D3.js

hangzhou_house_knowledge

2017年买房经历总结出来的买房购房知识分享给大家，希望对大家有所帮助。买房不易，且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.

jm-huang

line

LINE in Tensorflow

machine_learning_resources

:fish::fish::fish: 机器学习面试复习资源

natural-language-processing

nips2017

A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017

probabilistic-matrix-factorization

Python Implementation of Probabilistic Matrix Factorization(PMF) Algorithm for building a recommendation system using MovieLens ml-100k | GroupLens dataset

rgcnn

Neural Recommender System from "Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks"

stratipy

Graph regularized nonnegative matrix factorization (GNMF) in Python

sublime_text3_profile

top

Transductive Learning over the Product Graph. C++ Implementation

vimrc

the vimrc file

word2vec

This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.