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Name: Chen Chen

Type: User

Company: The State Key Laboratory of Integrated Services Networks, Xidian University

Bio: My name is Chen Chen. Currently a doctoral student at Xidian University. My major is artificial intelligence and my direction is cross-modal retrieval.

Chen Chen's Projects

adsh_pytorch icon adsh_pytorch

source code for paper "Asymmetric Deep Supervised Hashing" on AAAI-2018

clustergcn icon clustergcn

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

deep-mihash icon deep-mihash

Code for papers "Hashing with Mutual Information" (TPAMI 2019) and "Hashing with Binary Matrix Pursuit" (ECCV 2018)

dihn icon dihn

source code for paper "Deep Incremental Hashing Network for Efficient Image Retrieval" on CVPR-2019

download icon download

Lantern官方版本下载 蓝灯 翻墙 科学上网 外网 加速器 梯子 路由

dsh_tensorflow icon dsh_tensorflow

implemement of DEEP SUPERVISED HASHING FOR FAST IMAGE RETRIEVAL_CVPR2016

gce-gnn icon gce-gnn

The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".

gcmc icon gcmc

PyTorch and PyTorch geometric based implementation of Graph Convolutional Matrix Completion.

keras-textclassification icon keras-textclassification

中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM

kgcn icon kgcn

A tensorflow implementation of Knowledge Graph Convolutional Networks

models icon models

Models and examples built with TensorFlow

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch_deephash icon pytorch_deephash

Pytorch implementation of Deep Learning of Binary Hash Codes for Fast Image Retrieval, CVPRW 2015

recsys2019_deeplearning_evaluation icon recsys2019_deeplearning_evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches"

rspapers icon rspapers

Must-read papers on Recommender System.

sr-gnn icon sr-gnn

Source code and datasets for the paper "Session-based Recommendation with Graph Neural Networks" (AAAI-19)

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