Artículos de revistas sobre el tema "Graph attention network (GAT)"
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Wu, Nan y Chaofan Wang. "Ensemble Graph Attention Networks". Transactions on Machine Learning and Artificial Intelligence 10, n.º 3 (12 de junio de 2022): 29–41. http://dx.doi.org/10.14738/tmlai.103.12399.
Texto completoVerma, Atul Kumar, Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja y Jerry Chun-Wei Lin. "Bet-GAT: An Efficient Centrality-Based Graph Attention Model for Semi-Supervised Node Classification". Applied Sciences 13, n.º 2 (7 de enero de 2023): 847. http://dx.doi.org/10.3390/app13020847.
Texto completoLu, Shengfu, Jiaming Kang, Jinyu Zhang y Mi Li. "Assessment method of depressive disorder level based on graph attention network". ITM Web of Conferences 45 (2022): 01039. http://dx.doi.org/10.1051/itmconf/20224501039.
Texto completoXiang, Zhijie, Weijia Gong, Zehui Li, Xue Yang, Jihua Wang y Hong Wang. "Predicting Protein–Protein Interactions via Gated Graph Attention Signed Network". Biomolecules 11, n.º 6 (28 de mayo de 2021): 799. http://dx.doi.org/10.3390/biom11060799.
Texto completoYuan, Hong, Jing Huang y Jin Li. "Protein-ligand binding affinity prediction model based on graph attention network". Mathematical Biosciences and Engineering 18, n.º 6 (2021): 9148–62. http://dx.doi.org/10.3934/mbe.2021451.
Texto completoJing, Weipeng, Xianyang Song, Donglin Di y Houbing Song. "geoGAT: Graph Model Based on Attention Mechanism for Geographic Text Classification". ACM Transactions on Asian and Low-Resource Language Information Processing 20, n.º 5 (30 de septiembre de 2021): 1–18. http://dx.doi.org/10.1145/3434239.
Texto completoLiu, Yiwen, Tao Wen y Zhenning Wu. "Motion Artifact Detection Based on Regional–Temporal Graph Attention Network from Head Computed Tomography Images". Electronics 13, n.º 4 (10 de febrero de 2024): 724. http://dx.doi.org/10.3390/electronics13040724.
Texto completoHuang, Ling, Xing-Xing Liu, Shu-Qiang Huang, Chang-Dong Wang, Wei Tu, Jia-Meng Xie, Shuai Tang y Wendi Xie. "Temporal Hierarchical Graph Attention Network for Traffic Prediction". ACM Transactions on Intelligent Systems and Technology 12, n.º 6 (31 de diciembre de 2021): 1–21. http://dx.doi.org/10.1145/3446430.
Texto completoSong, Kyungwoo, Yohan Jung, Dongjun Kim y Il-Chul Moon. "Implicit Kernel Attention". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 11 (18 de mayo de 2021): 9713–21. http://dx.doi.org/10.1609/aaai.v35i11.17168.
Texto completoZheng, Jing, Ziren Gao, Jingsong Ma, Jie Shen y Kang Zhang. "Deep Graph Convolutional Networks for Accurate Automatic Road Network Selection". ISPRS International Journal of Geo-Information 10, n.º 11 (11 de noviembre de 2021): 768. http://dx.doi.org/10.3390/ijgi10110768.
Texto completoLiu, Tong y Bojun Liu. "Next basket recommendation based on graph attention network and transformer". Journal of Physics: Conference Series 2303, n.º 1 (1 de julio de 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2303/1/012023.
Texto completoZhu, Taomei, Maria Jesus Lopez Boada y Beatriz Lopez Boada. "Adaptive Graph Attention and Long Short-Term Memory-Based Networks for Traffic Prediction". Mathematics 12, n.º 2 (12 de enero de 2024): 255. http://dx.doi.org/10.3390/math12020255.
Texto completoDeng, Xuan, Cheng Zhang, Jian Shi y Zizhao Wu. "PU-GAT: Point cloud upsampling with graph attention network". Graphical Models 130 (diciembre de 2023): 101201. http://dx.doi.org/10.1016/j.gmod.2023.101201.
Texto completoZhao, Yanna, Gaobo Zhang, Changxu Dong, Qi Yuan, Fangzhou Xu y Yuanjie Zheng. "Graph Attention Network with Focal Loss for Seizure Detection on Electroencephalography Signals". International Journal of Neural Systems 31, n.º 07 (18 de mayo de 2021): 2150027. http://dx.doi.org/10.1142/s0129065721500271.
Texto completoPu, S., Y. Song, Y. Chen, Y. Li, J. Zhang, Q. Lin, X. Zhu et al. "HYPERSPECTRAL IMAGE CLASSIFICATION WITH LOCALIZED SPECTRAL FILTERING-BASED GRAPH ATTENTION NETWORK". ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (17 de mayo de 2022): 155–61. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-155-2022.
Texto completoWang, Renping, Shun Li, Enhao Tang, Sen Lan, Yajing Liu, Jing Yang, Shizhen Huang y Hailong Hu. "SH-GAT: Software-hardware co-design for accelerating graph attention networks on FPGA". Electronic Research Archive 32, n.º 4 (2024): 2310–22. http://dx.doi.org/10.3934/era.2024105.
Texto completoLin, Yu-Chen, Chia-Hung Wang y Yu-Cheng Lin. "GAT TransPruning: progressive channel pruning strategy combining graph attention network and transformer". PeerJ Computer Science 10 (23 de abril de 2024): e2012. http://dx.doi.org/10.7717/peerj-cs.2012.
Texto completoBian, Chen, Xiu-Juan Lei y Fang-Xiang Wu. "GATCDA: Predicting circRNA-Disease Associations Based on Graph Attention Network". Cancers 13, n.º 11 (25 de mayo de 2021): 2595. http://dx.doi.org/10.3390/cancers13112595.
Texto completoZhao, Mengmeng, Haipeng Peng, Lixiang Li y Yeqing Ren. "Graph Attention Network and Informer for Multivariate Time Series Anomaly Detection". Sensors 24, n.º 5 (26 de febrero de 2024): 1522. http://dx.doi.org/10.3390/s24051522.
Texto completoTanvir, Raihanul Bari, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo y Ananda Mohan Mondal. "MOGAT: A Multi-Omics Integration Framework Using Graph Attention Networks for Cancer Subtype Prediction". International Journal of Molecular Sciences 25, n.º 5 (28 de febrero de 2024): 2788. http://dx.doi.org/10.3390/ijms25052788.
Texto completoLv, Shaoqing, Jungang Dong, Chichi Wang, Xuanhong Wang y Zhiqiang Bao. "RB-GAT: A Text Classification Model Based on RoBERTa-BiGRU with Graph ATtention Network". Sensors 24, n.º 11 (24 de mayo de 2024): 3365. http://dx.doi.org/10.3390/s24113365.
Texto completoLei, Zengyu, Caiming Zhang, Yunyang Xu y Xuemei Li. "DR-GAT: Dynamic routing graph attention network for stock recommendation". Information Sciences 654 (enero de 2024): 119833. http://dx.doi.org/10.1016/j.ins.2023.119833.
Texto completoWan, Qizhi, Changxuan Wan, Keli Xiao, Kun Lu, Chenliang Li, Xiping Liu y Dexi Liu. "Dependency Structure-Enhanced Graph Attention Networks for Event Detection". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 17 (24 de marzo de 2024): 19098–106. http://dx.doi.org/10.1609/aaai.v38i17.29877.
Texto completoYang, Wu-Lue, Xiao-Ze Chen y Xu-Hua Yang. "Semisupervised Classification with High-Order Graph Learning Attention Neural Network". Mathematical Problems in Engineering 2021 (7 de diciembre de 2021): 1–10. http://dx.doi.org/10.1155/2021/3911137.
Texto completoCai, Fengze, Qiang Hu, Renjie Zhou y Neal Xiong. "REEGAT: RoBERTa Entity Embedding and Graph Attention Networks Enhanced Sentence Representation for Relation Extraction". Electronics 12, n.º 11 (27 de mayo de 2023): 2429. http://dx.doi.org/10.3390/electronics12112429.
Texto completoCui, Wei, Xin He, Meng Yao, Ziwei Wang, Yuanjie Hao, Jie Li, Weijie Wu et al. "Knowledge and Spatial Pyramid Distance-Based Gated Graph Attention Network for Remote Sensing Semantic Segmentation". Remote Sensing 13, n.º 7 (30 de marzo de 2021): 1312. http://dx.doi.org/10.3390/rs13071312.
Texto completoCao, Hailin, Wang Zhu, Wenjuan Feng y Jin Fan. "Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications". Entropy 24, n.º 3 (24 de febrero de 2022): 326. http://dx.doi.org/10.3390/e24030326.
Texto completoYang, Xiaohui, Hailong Ma y Miao Wang. "Research on Rumor Detection Based on a Graph Attention Network With Temporal Features". International Journal of Data Warehousing and Mining 19, n.º 2 (2 de marzo de 2023): 1–17. http://dx.doi.org/10.4018/ijdwm.319342.
Texto completoCao, Ruifen, Chuan He, Pijing Wei, Yansen Su, Junfeng Xia y Chunhou Zheng. "Prediction of circRNA-Disease Associations Based on the Combination of Multi-Head Graph Attention Network and Graph Convolutional Network". Biomolecules 12, n.º 7 (2 de julio de 2022): 932. http://dx.doi.org/10.3390/biom12070932.
Texto completoYağci, Mehmet Yavuz y Muhammed Ali Aydin. "EA-GAT: Event aware graph attention network on cyber-physical systems". Computers in Industry 159-160 (agosto de 2024): 104097. http://dx.doi.org/10.1016/j.compind.2024.104097.
Texto completoZhang, Yuhang, Yaoqun Xu y Yu Zhang. "A Graph Neural Network Node Classification Application Model with Enhanced Node Association". Applied Sciences 13, n.º 12 (15 de junio de 2023): 7150. http://dx.doi.org/10.3390/app13127150.
Texto completoYe, Haonan y Xiao Luo. "Cascading Failure Analysis on Shanghai Metro Networks: An Improved Coupled Map Lattices Model Based on Graph Attention Networks". International Journal of Environmental Research and Public Health 19, n.º 1 (25 de diciembre de 2021): 204. http://dx.doi.org/10.3390/ijerph19010204.
Texto completoLi, Yansheng, Ruixian Chen, Yongjun Zhang, Mi Zhang y Ling Chen. "Multi-Label Remote Sensing Image Scene Classification by Combining a Convolutional Neural Network and a Graph Neural Network". Remote Sensing 12, n.º 23 (7 de diciembre de 2020): 4003. http://dx.doi.org/10.3390/rs12234003.
Texto completoMu, Jichong, Jihong Ouyang, Yachen Yao y Zongxiao Ren. "Span-Prototype Graph Based on Graph Attention Network for Nested Named Entity Recognition". Electronics 12, n.º 23 (23 de noviembre de 2023): 4753. http://dx.doi.org/10.3390/electronics12234753.
Texto completoYang, Xiaohui, Hailong Ma y Miao Wang. "Rumor Detection with Bidirectional Graph Attention Networks". Security and Communication Networks 2022 (18 de enero de 2022): 1–13. http://dx.doi.org/10.1155/2022/4840997.
Texto completoJi, Cunmei, Zhihao Liu, Yutian Wang, Jiancheng Ni y Chunhou Zheng. "GATNNCDA: A Method Based on Graph Attention Network and Multi-Layer Neural Network for Predicting circRNA-Disease Associations". International Journal of Molecular Sciences 22, n.º 16 (7 de agosto de 2021): 8505. http://dx.doi.org/10.3390/ijms22168505.
Texto completoBaul, Sudipto, Khandakar Tanvir Ahmed, Joseph Filipek y Wei Zhang. "omicsGAT: Graph Attention Network for Cancer Subtype Analyses". International Journal of Molecular Sciences 23, n.º 18 (6 de septiembre de 2022): 10220. http://dx.doi.org/10.3390/ijms231810220.
Texto completoWu, Xingping, Qiheng Yuan, Chunlei Zhou, Xiang Chen, Donghai Xuan y Jinwei Song. "Carbon emissions forecasting based on temporal graph transformer-based attentional neural network". Journal of Computational Methods in Sciences and Engineering 24, n.º 3 (17 de junio de 2024): 1405–21. http://dx.doi.org/10.3233/jcm-247139.
Texto completoAlothali, Eiman, Motamen Salih, Kadhim Hayawi y Hany Alashwal. "Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots". Applied Sciences 12, n.º 16 (13 de agosto de 2022): 8117. http://dx.doi.org/10.3390/app12168117.
Texto completoWei, Pengfei, Bi Zeng y Wenxiong Liao. "Joint intent detection and slot filling with wheel-graph attention networks". Journal of Intelligent & Fuzzy Systems 42, n.º 3 (2 de febrero de 2022): 2409–20. http://dx.doi.org/10.3233/jifs-211674.
Texto completoZhao, Mingxiu, Jing Zhang, Qin Li, Junzheng Yang, Estevao Siga y Tianchi Zhang. "GAT-ABiGRU Based Prediction Model for AUV Trajectory". Applied Sciences 14, n.º 10 (15 de mayo de 2024): 4184. http://dx.doi.org/10.3390/app14104184.
Texto completoUmair, Muhammad, Iftikhar Alam, Atif Khan, Inayat Khan, Niamat Ullah y Mohammad Yusuf Momand. "N-GPETS: Neural Attention Graph-Based Pretrained Statistical Model for Extractive Text Summarization". Computational Intelligence and Neuroscience 2022 (22 de noviembre de 2022): 1–14. http://dx.doi.org/10.1155/2022/6241373.
Texto completoChen, Yang, Weibing Wan, Jimi Hu, Yuxuan Wang y Bo Huang. "Complex Causal Extraction of Fusion of Entity Location Sensing and Graph Attention Networks". Information 13, n.º 8 (31 de julio de 2022): 364. http://dx.doi.org/10.3390/info13080364.
Texto completoZhou, Hang, Weikun Wang, Jiayun Jin, Zengwei Zheng y Binbin Zhou. "Graph Neural Network for Protein–Protein Interaction Prediction: A Comparative Study". Molecules 27, n.º 18 (19 de septiembre de 2022): 6135. http://dx.doi.org/10.3390/molecules27186135.
Texto completoShao, Yingzhao, Yunsong Li, Li Li, Yuanle Wang, Yuchen Yang, Yueli Ding, Mingming Zhang, Yang Liu y Xiangqiang Gao. "RANet: Relationship Attention for Hyperspectral Anomaly Detection". Remote Sensing 15, n.º 23 (30 de noviembre de 2023): 5570. http://dx.doi.org/10.3390/rs15235570.
Texto completoGao, Yunmeng, Liang Zhao, Jin Du y Junnan Wang. "Spatial-temporal Traffic Flow Prediction Model Based on the GAT and BiGRU". Journal of Physics: Conference Series 2589, n.º 1 (1 de septiembre de 2023): 012024. http://dx.doi.org/10.1088/1742-6596/2589/1/012024.
Texto completoXu, Dawei, Qing Liu, Liehuang Zhu, Zhonghua Tan, Feng Gao y Jian Zhao. "GCNRDM: A Social Network Rumor Detection Method Based on Graph Convolutional Network in Mobile Computing". Wireless Communications and Mobile Computing 2021 (8 de octubre de 2021): 1–11. http://dx.doi.org/10.1155/2021/1690669.
Texto completoPeng, Feifei, Wei Lu, Wenxia Tan, Kunlun Qi, Xiaokang Zhang y Quansheng Zhu. "Multi-Output Network Combining GNN and CNN for Remote Sensing Scene Classification". Remote Sensing 14, n.º 6 (18 de marzo de 2022): 1478. http://dx.doi.org/10.3390/rs14061478.
Texto completoCui, Wei, Yuanjie Hao, Xing Xu, Zhanyun Feng, Huilin Zhao, Cong Xia y Jin Wang. "Remote Sensing Scene Graph and Knowledge Graph Matching with Parallel Walking Algorithm". Remote Sensing 14, n.º 19 (29 de septiembre de 2022): 4872. http://dx.doi.org/10.3390/rs14194872.
Texto completoZhan, Huixin, Kun Zhang, Keyi Lu y Victor S. Sheng. "Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 13 (26 de junio de 2023): 16380–81. http://dx.doi.org/10.1609/aaai.v37i13.27050.
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