Pinned Repositories
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
jm-huang's Repositories
jm-huang/jm-huang
jm-huang/Machine_Learning_Resources
:fish::fish::fish: 机器学习面试复习资源
jm-huang/2015lab1
jm-huang/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].
jm-huang/CF-NADE
A implementation of CF-NADE. Yin Zheng, et. al. "A Neural Autoregressive Approach to Collaborative Filtering", accepted by ICML 2016.
jm-huang/GCMC
Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction
jm-huang/gcn
Implementation of Graph Convolutional Networks in TensorFlow
jm-huang/graphexp
Interactive visualization of the Gremlin graph database with D3.js
jm-huang/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
jm-huang/Natural-Language-Processing
jm-huang/nips2017
A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017
jm-huang/Probabilistic-Matrix-Factorization
Python Implementation of Probabilistic Matrix Factorization(PMF) Algorithm for building a recommendation system using MovieLens ml-100k | GroupLens dataset
jm-huang/rgcnn
Neural Recommender System from "Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks"
jm-huang/StratiPy
Graph regularized nonnegative matrix factorization (GNMF) in Python
jm-huang/sublime_text3_profile
jm-huang/TOP
Transductive Learning over the Product Graph. C++ Implementation
jm-huang/vimrc
the vimrc file
jm-huang/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.