Статті в журналах з теми "Graph and Multi-view Memory Attention"
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Ai, Bing, Yibing Wang, Liang Ji, Jia Yi, Ting Wang, Wentao Liu, and Hui Zhou. "A graph neural network fused with multi-head attention for text classification." Journal of Physics: Conference Series 2132, no. 1 (December 1, 2021): 012032. http://dx.doi.org/10.1088/1742-6596/2132/1/012032.
Повний текст джерелаLiu, Di, Hui Xu, Jianzhong Wang, Yinghua Lu, Jun Kong, and Miao Qi. "Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition." Sensors 21, no. 20 (October 12, 2021): 6761. http://dx.doi.org/10.3390/s21206761.
Повний текст джерелаFeng, Aosong, Irene Li, Yuang Jiang, and Rex Ying. "Diffuser: Efficient Transformers with Multi-Hop Attention Diffusion for Long Sequences." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (June 26, 2023): 12772–80. http://dx.doi.org/10.1609/aaai.v37i11.26502.
Повний текст джерелаLi, Mingxiao, and Marie-Francine Moens. "Dynamic Key-Value Memory Enhanced Multi-Step Graph Reasoning for Knowledge-Based Visual Question Answering." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (June 28, 2022): 10983–92. http://dx.doi.org/10.1609/aaai.v36i10.21346.
Повний текст джерелаJung, Tae-Won, Chi-Seo Jeong, In-Seon Kim, Min-Su Yu, Soon-Chul Kwon, and Kye-Dong Jung. "Graph Convolutional Network for 3D Object Pose Estimation in a Point Cloud." Sensors 22, no. 21 (October 25, 2022): 8166. http://dx.doi.org/10.3390/s22218166.
Повний текст джерелаCui, Wei, Fei Wang, Xin He, Dongyou Zhang, Xuxiang Xu, Meng Yao, Ziwei Wang, and Jiejun Huang. "Multi-Scale Semantic Segmentation and Spatial Relationship Recognition of Remote Sensing Images Based on an Attention Model." Remote Sensing 11, no. 9 (May 2, 2019): 1044. http://dx.doi.org/10.3390/rs11091044.
Повний текст джерелаHou, Miaomiao, Xiaofeng Hu, Jitao Cai, Xinge Han, and Shuaiqi Yuan. "An Integrated Graph Model for Spatial–Temporal Urban Crime Prediction Based on Attention Mechanism." ISPRS International Journal of Geo-Information 11, no. 5 (April 30, 2022): 294. http://dx.doi.org/10.3390/ijgi11050294.
Повний текст джерелаMi, Chunlei, Shifen Cheng, and Feng Lu. "Predicting Taxi-Calling Demands Using Multi-Feature and Residual Attention Graph Convolutional Long Short-Term Memory Networks." ISPRS International Journal of Geo-Information 11, no. 3 (March 9, 2022): 185. http://dx.doi.org/10.3390/ijgi11030185.
Повний текст джерелаKarimanzira, Divas, Linda Ritzau, and Katharina Emde. "Catchment Area Multi-Streamflow Multiple Hours Ahead Forecast Based on Deep Learning." Transactions on Machine Learning and Artificial Intelligence 10, no. 5 (September 29, 2022): 15–29. http://dx.doi.org/10.14738/tmlai.105.13049.
Повний текст джерелаWang, Changhai, Jiaxi Ren, and Hui Liang. "MSGraph: Modeling multi-scale K-line sequences with graph attention network for profitable indices recommendation." Electronic Research Archive 31, no. 5 (2023): 2626–50. http://dx.doi.org/10.3934/era.2023133.
Повний текст джерелаMa, Xinwei, Yurui Yin, Yuchuan Jin, Mingjia He, and Minqing Zhu. "Short-Term Prediction of Bike-Sharing Demand Using Multi-Source Data: A Spatial-Temporal Graph Attentional LSTM Approach." Applied Sciences 12, no. 3 (January 23, 2022): 1161. http://dx.doi.org/10.3390/app12031161.
Повний текст джерелаLin, Chun, Yijia Xu, Yong Fang, and Zhonglin Liu. "VulEye: A Novel Graph Neural Network Vulnerability Detection Approach for PHP Application." Applied Sciences 13, no. 2 (January 6, 2023): 825. http://dx.doi.org/10.3390/app13020825.
Повний текст джерелаLiu, Daizong, Xiaoye Qu, Xing Di, Yu Cheng, Zichuan Xu, and Pan Zhou. "Memory-Guided Semantic Learning Network for Temporal Sentence Grounding." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (June 28, 2022): 1665–73. http://dx.doi.org/10.1609/aaai.v36i2.20058.
Повний текст джерелаWu, Jie, Ian G. Harris, and Hongzhi Zhao. "GraphMemDialog: Optimizing End-to-End Task-Oriented Dialog Systems Using Graph Memory Networks." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (June 28, 2022): 11504–12. http://dx.doi.org/10.1609/aaai.v36i10.21403.
Повний текст джерелаLiu, Yuanxin, Delei Tian, and Bin Zheng. "Non-communicating Decentralized Multi-robot Collision Avoidance in Grid Graph Workspace based on Dueling Double Deep Q-Network." Journal of Physics: Conference Series 2456, no. 1 (March 1, 2023): 012015. http://dx.doi.org/10.1088/1742-6596/2456/1/012015.
Повний текст джерелаSu, Guimin, Zimu Zeng, Andi Song, Cong Zhao, Feng Shen, Liangxiao Yuan, and Xinghua Li. "A General Framework for Reconstructing Full-Sample Continuous Vehicle Trajectories Using Roadside Sensing Data." Applied Sciences 13, no. 5 (February 28, 2023): 3141. http://dx.doi.org/10.3390/app13053141.
Повний текст джерелаHu, Zhangfang, Libujie Chen, Yuan Luo, and Jingfan Zhou. "EEG-Based Emotion Recognition Using Convolutional Recurrent Neural Network with Multi-Head Self-Attention." Applied Sciences 12, no. 21 (November 6, 2022): 11255. http://dx.doi.org/10.3390/app122111255.
Повний текст джерелаJi, Zhanhao, Guojiang Shen, Juntao Wang, Mario Collotta, Zhi Liu, and Xiangjie Kong. "Multi-Vehicle Trajectory Tracking towards Digital Twin Intersections for Internet of Vehicles." Electronics 12, no. 2 (January 5, 2023): 275. http://dx.doi.org/10.3390/electronics12020275.
Повний текст джерелаJin, Yanliang, Jinjin Ye, Liquan Shen, Yong Xiong, Lele Fan, and Qingfu Zang. "Hierarchical Attention Neural Network for Event Types to Improve Event Detection." Sensors 22, no. 11 (May 31, 2022): 4202. http://dx.doi.org/10.3390/s22114202.
Повний текст джерелаTian, Qi, Kun Kuang, Furui Liu, and Baoxiang Wang. "Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 10 (June 26, 2023): 11672–80. http://dx.doi.org/10.1609/aaai.v37i10.26379.
Повний текст джерелаYang, Shuai, Yueqin Zhang, and Zehua Zhang. "Runoff Prediction Based on Dynamic Spatiotemporal Graph Neural Network." Water 15, no. 13 (July 5, 2023): 2463. http://dx.doi.org/10.3390/w15132463.
Повний текст джерелаLi, Youru, Zhenfeng Zhu, Deqiang Kong, Meixiang Xu, and Yao Zhao. "Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1004–11. http://dx.doi.org/10.1609/aaai.v33i01.33011004.
Повний текст джерелаLiu, Lijuan, Mingxiao Wu, Rung-Ching Chen, Shunzhi Zhu, and Yan Wang. "A Hybrid Deep Learning Model for Multi-Station Classification and Passenger Flow Prediction." Applied Sciences 13, no. 5 (February 23, 2023): 2899. http://dx.doi.org/10.3390/app13052899.
Повний текст джерелаChen, Yun, Chengwei Liang, Dengcheng Liu, Qingren Niu, Xinke Miao, Guangyu Dong, Liguang Li, Shanbin Liao, Xiaoci Ni, and Xiaobo Huang. "Embedding-Graph-Neural-Network for Transient NOx Emissions Prediction." Energies 16, no. 1 (December 20, 2022): 3. http://dx.doi.org/10.3390/en16010003.
Повний текст джерелаUddin, Md Azher, Joolekha Bibi Joolee, Young-Koo Lee, and Kyung-Ah Sohn. "A Novel Multi-Modal Network-Based Dynamic Scene Understanding." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 1 (January 31, 2022): 1–19. http://dx.doi.org/10.1145/3462218.
Повний текст джерелаZhou, Hang, Junqing Yu, and Wei Yang. "Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (June 26, 2023): 3769–77. http://dx.doi.org/10.1609/aaai.v37i3.25489.
Повний текст джерелаZhang, Suqi, Xinxin Wang, Wenfeng Wang, Ningjing Zhang, Yunhao Fang, and Jianxin Li. "Recommendation model based on intention decomposition and heterogeneous information fusion." Mathematical Biosciences and Engineering 20, no. 9 (2023): 16401–20. http://dx.doi.org/10.3934/mbe.2023732.
Повний текст джерелаFang, Ziquan, Lu Pan, Lu Chen, Yuntao Du, and Yunjun Gao. "MDTP." Proceedings of the VLDB Endowment 14, no. 8 (April 2021): 1289–97. http://dx.doi.org/10.14778/3457390.3457394.
Повний текст джерелаXie, Yu, Yuanqiao Zhang, Maoguo Gong, Zedong Tang, and Chao Han. "MGAT: Multi-view Graph Attention Networks." Neural Networks 132 (December 2020): 180–89. http://dx.doi.org/10.1016/j.neunet.2020.08.021.
Повний текст джерелаYao, Kaixuan, Jiye Liang, Jianqing Liang, Ming Li, and Feilong Cao. "Multi-view graph convolutional networks with attention mechanism." Artificial Intelligence 307 (June 2022): 103708. http://dx.doi.org/10.1016/j.artint.2022.103708.
Повний текст джерелаChen, Lei, Jie Cao, Youquan Wang, Weichao Liang, and Guixiang Zhu. "Multi-view Graph Attention Network for Travel Recommendation." Expert Systems with Applications 191 (April 2022): 116234. http://dx.doi.org/10.1016/j.eswa.2021.116234.
Повний текст джерелаZhang, Pengyu, Yong Zhang, Jingcheng Wang, and Baocai Yin. "MVMA-GCN: Multi-view multi-layer attention graph convolutional networks." Engineering Applications of Artificial Intelligence 126 (November 2023): 106717. http://dx.doi.org/10.1016/j.engappai.2023.106717.
Повний текст джерелаPoologaindran, Anujan, Mike Hart, Tom Santarius, Stephen Price, Rohit Sinha, Mike Sughrue, Yaara Erez, Rafael Romero-Garcia, and John Suckling. "Longitudinal Connectome Analyses following Low-Grade Glioma Neurosurgery: Implications for Cognitive Rehabilitation." Neuro-Oncology 23, Supplement_4 (October 1, 2021): iv8. http://dx.doi.org/10.1093/neuonc/noab195.015.
Повний текст джерелаTang, Chang, Xinwang Liu, Xinzhong Zhu, En Zhu, Zhigang Luo, Lizhe Wang, and Wen Gao. "CGD: Multi-View Clustering via Cross-View Graph Diffusion." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 5924–31. http://dx.doi.org/10.1609/aaai.v34i04.6052.
Повний текст джерелаZhu, Fujian, and Shaojie Dai. "Multi-view Attention Mechanism Learning for POI Recommendation." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012041. http://dx.doi.org/10.1088/1742-6596/2258/1/012041.
Повний текст джерелаZou, Yongqi, Wenjiang Feng, Juntao Zhang, and Jingfu Li. "Forecasting of Short-Term Load Using the MFF-SAM-GCN Model." Energies 15, no. 9 (April 25, 2022): 3140. http://dx.doi.org/10.3390/en15093140.
Повний текст джерелаZou, Yongqi, Wenjiang Feng, Juntao Zhang, and Jingfu Li. "Forecasting of Short-Term Load Using the MFF-SAM-GCN Model." Energies 15, no. 9 (April 25, 2022): 3140. http://dx.doi.org/10.3390/en15093140.
Повний текст джерелаWu, Fei, Changjiang Zheng, Chen Zhang, Junze Ma, and Kai Sun. "Multi-View Multi-Attention Graph Neural Network for Traffic Flow Forecasting." Applied Sciences 13, no. 2 (January 4, 2023): 711. http://dx.doi.org/10.3390/app13020711.
Повний текст джерелаCui, Wanqiu, Junping Du, Dawei Wang, Feifei Kou, and Zhe Xue. "MVGAN: Multi-View Graph Attention Network for Social Event Detection." ACM Transactions on Intelligent Systems and Technology 12, no. 3 (July 19, 2021): 1–24. http://dx.doi.org/10.1145/3447270.
Повний текст джерелаHuang, Zongmo, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, and Lifang He. "Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (June 26, 2023): 7936–43. http://dx.doi.org/10.1609/aaai.v37i7.25960.
Повний текст джерелаWang, Li, Xin Wang, and Jiao Wang. "Rail Transit Prediction Based on Multi-View Graph Attention Networks." Journal of Advanced Transportation 2022 (July 6, 2022): 1–8. http://dx.doi.org/10.1155/2022/4672617.
Повний текст джерелаLing, Yawen, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, and Lifang He. "Dual Label-Guided Graph Refinement for Multi-View Graph Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (June 26, 2023): 8791–98. http://dx.doi.org/10.1609/aaai.v37i7.26057.
Повний текст джерелаLyu, Gengyu, Xiang Deng, Yanan Wu, and Songhe Feng. "Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (June 28, 2022): 7647–54. http://dx.doi.org/10.1609/aaai.v36i7.20731.
Повний текст джерелаZhang, Pei, Siwei Wang, Jingtao Hu, Zhen Cheng, Xifeng Guo, En Zhu, and Zhiping Cai. "Adaptive Weighted Graph Fusion Incomplete Multi-View Subspace Clustering." Sensors 20, no. 20 (October 10, 2020): 5755. http://dx.doi.org/10.3390/s20205755.
Повний текст джерелаShang, Chao, Qinqing Liu, Qianqian Tong, Jiangwen Sun, Minghu Song, and Jinbo Bi. "Multi-view spectral graph convolution with consistent edge attention for molecular modeling." Neurocomputing 445 (July 2021): 12–25. http://dx.doi.org/10.1016/j.neucom.2021.02.025.
Повний текст джерелаYu, Jinshi, Qi Duan, Haonan Huang, Shude He, and Tao Zou. "Effective Incomplete Multi-View Clustering via Low-Rank Graph Tensor Completion." Mathematics 11, no. 3 (January 28, 2023): 652. http://dx.doi.org/10.3390/math11030652.
Повний текст джерелаHuang, Yanquan, Haoliang Yuan, and Loi Lei Lai. "Latent multi-view semi-supervised classification by using graph learning." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 05 (June 20, 2020): 2050039. http://dx.doi.org/10.1142/s0219691320500393.
Повний текст джерелаAlothali, Eiman, Motamen Salih, Kadhim Hayawi, and Hany Alashwal. "Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots." Applied Sciences 12, no. 16 (August 13, 2022): 8117. http://dx.doi.org/10.3390/app12168117.
Повний текст джерелаZeng, Hui, Tianmeng Zhao, Ruting Cheng, Fuzhou Wang, and Jiwei Liu. "Hierarchical Graph Attention Based Multi-View Convolutional Neural Network for 3D Object Recognition." IEEE Access 9 (2021): 33323–35. http://dx.doi.org/10.1109/access.2021.3059853.
Повний текст джерелаZhu, Jiangqiang, Kai Li, Jinjia Peng, and Jing Qi. "Self-Supervised Graph Attention Collaborative Filtering for Recommendation." Electronics 12, no. 4 (February 5, 2023): 793. http://dx.doi.org/10.3390/electronics12040793.
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