中国科学院计算技术研究所机构知识库

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限定条件	文献类型：期刊论文    专题：中国科学院计算技术研究所期刊论文    第一作者的第一单位    第一作者单位    通讯作者单位

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择期刊影响因子升序期刊影响因子降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序WOS被引频次升序WOS被引频次降序题名升序题名降序
	Dynamic graph neural network-based fraud detectors against collaborative fraudsters 期刊论文 KNOWLEDGE-BASED SYSTEMS, 2023, 卷号: 278, 页码: 12 作者:  Ren, Lingfei;  Hu, Ruimin;  Li, Dengshi;  Liu, Yang;  Wu, Junhang;  Zang, Yilong;  Hu, Wenyi 收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04 Telecom fraud detection  Collaborative fraud  Semi -supervised learning  Dynamic graph neural network
	DiamondNet: A Neural-Network-Based Heterogeneous Sensor Attentive Fusion for Human Activity Recognition 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 11 作者:  Zhu, Yida;  Luo, Haiyong;  Chen, Runze;  Zhao, Fang 收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04 Convolutional denoising autoencoders (CDAEs)  global-attention mechanism  graph convolutional networks  human activity recognition (HAR)  multisensor modality  self-attention mechanism
	Research on Multi-Port Ship Traffic Prediction Method Based on Spatiotemporal Graph Neural Networks 期刊论文 JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 卷号: 11, 期号: 7, 页码: 18 作者:  Li, Yong;  Li, Zhaoxuan;  Mei, Qiang;  Wang, Peng;  Hu, Wenlong;  Wang, Zhishan;  Xie, Wenxin;  Yang, Yang;  Chen, Yuhaoran 收藏  |  浏览/下载：7/0  |  提交时间：2023/12/04 spatiotemporal graph neural network  traffic flow prediction  ship big data  AIS  port traffic prediction
	Motif-GCNs With Local and Non-Local Temporal Blocks for Skeleton-Based Action Recognition 期刊论文 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 2, 页码: 2009-2023 作者:  Wen, Yu-Hui;  Gao, Lin;  Fu, Hongbo;  Zhang, Fang-Lue;  Xia, Shihong;  Liu, Yong-Jin 收藏  |  浏览/下载：13/0  |  提交时间：2023/07/12 Skeleton  Feature extraction  Joints  Convolutional codes  Topology  Training  Sparse matrices  Action recognition  graph convolutional neural networks  spatio-temporal attention  non-local block  skeleton sequence
	Optimus: An Operator Fusion Framework for Deep Neural Networks 期刊论文 ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2023, 卷号: 22, 期号: 1, 页码: 26 作者:  Cai, Xuyi;  Wang, Ying;  Zhang, Lei 收藏  |  浏览/下载：15/0  |  提交时间：2023/07/12 Neural network  embedded processor  memory  layer fusion
	Location-aware convolutional neural networks for graph classification 期刊论文 NEURAL NETWORKS, 2022, 卷号: 155, 页码: 74-83 作者:  Wang, Zhaohui;  Cao, Qi;  Shen, Huawei;  Xu, Bingbing;  Cen, Keting;  Cheng, Xueqi 收藏  |  浏览/下载：13/0  |  提交时间：2023/07/12 Graph classification  Convolutional neural networks  Location-aware
	Self-Supervised Enhancement for Named Entity Disambiguation via Multimodal Graph Convolution 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15 作者:  Zhou, Pengfei;  Ying, Kaining;  Wang, Zhenhua;  Guo, Dongyan;  Bai, Cong 收藏  |  浏览/下载：29/0  |  提交时间：2022/12/07 Task analysis  Convolution  Semantics  Internet  Bit error rate  Visualization  Pipelines  Graph convolutional network (GCN)  multimodal data  named entity disambiguation (NED)  self-supervised learning (SSL)
	Rubik: A Hierarchical Architecture for Efficient Graph Neural Network Training 期刊论文 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 4, 页码: 936-949 作者:  Chen, Xiaobing;  Wang, Yuke;  Xie, Xinfeng;  Hu, Xing;  Basak, Abanti;  Liang, Ling;  Yan, Mingyu;  Deng, Lei;  Ding, Yufei;  Du, Zidong;  Xie, Yuan 收藏  |  浏览/下载：21/0  |  提交时间：2022/12/07 Deep learning accelerator  graph neural network (GNN)
	SSGraphCPI: A Novel Model for Predicting Compound-Protein Interactions Based on Deep Learning 期刊论文 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2022, 卷号: 23, 期号: 7, 页码: 13 作者:  Wang, Xun;  Liu, Jiali;  Zhang, Chaogang;  Wang, Shudong 收藏  |  浏览/下载：23/0  |  提交时间：2022/12/07 deep learning  compound-protein interactions  compound properties  protein preperties  IC50 value
	Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 2, 页码: 205-234 作者:  Liu, Xin;  Yan, Mingyu;  Deng, Lei;  Li, Guoqi;  Ye, Xiaochun;  Fan, Dongrui 收藏  |  浏览/下载：30/0  |  提交时间：2022/06/21 Efficient training  graph convolutional networks (GCNs)  graph neural networks (GNNs)  sampling method