Artykuły w czasopismach na temat „Graph attention network (GAT)”
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Wu, Nan, i Chaofan Wang. "Ensemble Graph Attention Networks". Transactions on Machine Learning and Artificial Intelligence 10, nr 3 (12.06.2022): 29–41. http://dx.doi.org/10.14738/tmlai.103.12399.
Pełny tekst źródłaVerma, Atul Kumar, Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja i Jerry Chun-Wei Lin. "Bet-GAT: An Efficient Centrality-Based Graph Attention Model for Semi-Supervised Node Classification". Applied Sciences 13, nr 2 (7.01.2023): 847. http://dx.doi.org/10.3390/app13020847.
Pełny tekst źródłaLu, Shengfu, Jiaming Kang, Jinyu Zhang i 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.
Pełny tekst źródłaXiang, Zhijie, Weijia Gong, Zehui Li, Xue Yang, Jihua Wang i Hong Wang. "Predicting Protein–Protein Interactions via Gated Graph Attention Signed Network". Biomolecules 11, nr 6 (28.05.2021): 799. http://dx.doi.org/10.3390/biom11060799.
Pełny tekst źródłaYuan, Hong, Jing Huang i Jin Li. "Protein-ligand binding affinity prediction model based on graph attention network". Mathematical Biosciences and Engineering 18, nr 6 (2021): 9148–62. http://dx.doi.org/10.3934/mbe.2021451.
Pełny tekst źródłaJing, Weipeng, Xianyang Song, Donglin Di i Houbing Song. "geoGAT: Graph Model Based on Attention Mechanism for Geographic Text Classification". ACM Transactions on Asian and Low-Resource Language Information Processing 20, nr 5 (30.09.2021): 1–18. http://dx.doi.org/10.1145/3434239.
Pełny tekst źródłaLiu, Yiwen, Tao Wen i Zhenning Wu. "Motion Artifact Detection Based on Regional–Temporal Graph Attention Network from Head Computed Tomography Images". Electronics 13, nr 4 (10.02.2024): 724. http://dx.doi.org/10.3390/electronics13040724.
Pełny tekst źródłaHuang, Ling, Xing-Xing Liu, Shu-Qiang Huang, Chang-Dong Wang, Wei Tu, Jia-Meng Xie, Shuai Tang i Wendi Xie. "Temporal Hierarchical Graph Attention Network for Traffic Prediction". ACM Transactions on Intelligent Systems and Technology 12, nr 6 (31.12.2021): 1–21. http://dx.doi.org/10.1145/3446430.
Pełny tekst źródłaSong, Kyungwoo, Yohan Jung, Dongjun Kim i Il-Chul Moon. "Implicit Kernel Attention". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 11 (18.05.2021): 9713–21. http://dx.doi.org/10.1609/aaai.v35i11.17168.
Pełny tekst źródłaZheng, Jing, Ziren Gao, Jingsong Ma, Jie Shen i Kang Zhang. "Deep Graph Convolutional Networks for Accurate Automatic Road Network Selection". ISPRS International Journal of Geo-Information 10, nr 11 (11.11.2021): 768. http://dx.doi.org/10.3390/ijgi10110768.
Pełny tekst źródłaLiu, Tong, i Bojun Liu. "Next basket recommendation based on graph attention network and transformer". Journal of Physics: Conference Series 2303, nr 1 (1.07.2022): 012023. http://dx.doi.org/10.1088/1742-6596/2303/1/012023.
Pełny tekst źródłaZhu, Taomei, Maria Jesus Lopez Boada i Beatriz Lopez Boada. "Adaptive Graph Attention and Long Short-Term Memory-Based Networks for Traffic Prediction". Mathematics 12, nr 2 (12.01.2024): 255. http://dx.doi.org/10.3390/math12020255.
Pełny tekst źródłaDeng, Xuan, Cheng Zhang, Jian Shi i Zizhao Wu. "PU-GAT: Point cloud upsampling with graph attention network". Graphical Models 130 (grudzień 2023): 101201. http://dx.doi.org/10.1016/j.gmod.2023.101201.
Pełny tekst źródłaZhao, Yanna, Gaobo Zhang, Changxu Dong, Qi Yuan, Fangzhou Xu i Yuanjie Zheng. "Graph Attention Network with Focal Loss for Seizure Detection on Electroencephalography Signals". International Journal of Neural Systems 31, nr 07 (18.05.2021): 2150027. http://dx.doi.org/10.1142/s0129065721500271.
Pełny tekst źródłaPu, S., Y. Song, Y. Chen, Y. Li, J. Zhang, Q. Lin, X. Zhu i in. "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 (17.05.2022): 155–61. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-155-2022.
Pełny tekst źródłaWang, Renping, Shun Li, Enhao Tang, Sen Lan, Yajing Liu, Jing Yang, Shizhen Huang i Hailong Hu. "SH-GAT: Software-hardware co-design for accelerating graph attention networks on FPGA". Electronic Research Archive 32, nr 4 (2024): 2310–22. http://dx.doi.org/10.3934/era.2024105.
Pełny tekst źródłaLin, Yu-Chen, Chia-Hung Wang i Yu-Cheng Lin. "GAT TransPruning: progressive channel pruning strategy combining graph attention network and transformer". PeerJ Computer Science 10 (23.04.2024): e2012. http://dx.doi.org/10.7717/peerj-cs.2012.
Pełny tekst źródłaBian, Chen, Xiu-Juan Lei i Fang-Xiang Wu. "GATCDA: Predicting circRNA-Disease Associations Based on Graph Attention Network". Cancers 13, nr 11 (25.05.2021): 2595. http://dx.doi.org/10.3390/cancers13112595.
Pełny tekst źródłaZhao, Mengmeng, Haipeng Peng, Lixiang Li i Yeqing Ren. "Graph Attention Network and Informer for Multivariate Time Series Anomaly Detection". Sensors 24, nr 5 (26.02.2024): 1522. http://dx.doi.org/10.3390/s24051522.
Pełny tekst źródłaTanvir, Raihanul Bari, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo i Ananda Mohan Mondal. "MOGAT: A Multi-Omics Integration Framework Using Graph Attention Networks for Cancer Subtype Prediction". International Journal of Molecular Sciences 25, nr 5 (28.02.2024): 2788. http://dx.doi.org/10.3390/ijms25052788.
Pełny tekst źródłaLv, Shaoqing, Jungang Dong, Chichi Wang, Xuanhong Wang i Zhiqiang Bao. "RB-GAT: A Text Classification Model Based on RoBERTa-BiGRU with Graph ATtention Network". Sensors 24, nr 11 (24.05.2024): 3365. http://dx.doi.org/10.3390/s24113365.
Pełny tekst źródłaLei, Zengyu, Caiming Zhang, Yunyang Xu i Xuemei Li. "DR-GAT: Dynamic routing graph attention network for stock recommendation". Information Sciences 654 (styczeń 2024): 119833. http://dx.doi.org/10.1016/j.ins.2023.119833.
Pełny tekst źródłaWan, Qizhi, Changxuan Wan, Keli Xiao, Kun Lu, Chenliang Li, Xiping Liu i Dexi Liu. "Dependency Structure-Enhanced Graph Attention Networks for Event Detection". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 17 (24.03.2024): 19098–106. http://dx.doi.org/10.1609/aaai.v38i17.29877.
Pełny tekst źródłaYang, Wu-Lue, Xiao-Ze Chen i Xu-Hua Yang. "Semisupervised Classification with High-Order Graph Learning Attention Neural Network". Mathematical Problems in Engineering 2021 (7.12.2021): 1–10. http://dx.doi.org/10.1155/2021/3911137.
Pełny tekst źródłaCai, Fengze, Qiang Hu, Renjie Zhou i Neal Xiong. "REEGAT: RoBERTa Entity Embedding and Graph Attention Networks Enhanced Sentence Representation for Relation Extraction". Electronics 12, nr 11 (27.05.2023): 2429. http://dx.doi.org/10.3390/electronics12112429.
Pełny tekst źródłaCui, Wei, Xin He, Meng Yao, Ziwei Wang, Yuanjie Hao, Jie Li, Weijie Wu i in. "Knowledge and Spatial Pyramid Distance-Based Gated Graph Attention Network for Remote Sensing Semantic Segmentation". Remote Sensing 13, nr 7 (30.03.2021): 1312. http://dx.doi.org/10.3390/rs13071312.
Pełny tekst źródłaCao, Hailin, Wang Zhu, Wenjuan Feng i Jin Fan. "Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications". Entropy 24, nr 3 (24.02.2022): 326. http://dx.doi.org/10.3390/e24030326.
Pełny tekst źródłaYang, Xiaohui, Hailong Ma i Miao Wang. "Research on Rumor Detection Based on a Graph Attention Network With Temporal Features". International Journal of Data Warehousing and Mining 19, nr 2 (2.03.2023): 1–17. http://dx.doi.org/10.4018/ijdwm.319342.
Pełny tekst źródłaCao, Ruifen, Chuan He, Pijing Wei, Yansen Su, Junfeng Xia i Chunhou Zheng. "Prediction of circRNA-Disease Associations Based on the Combination of Multi-Head Graph Attention Network and Graph Convolutional Network". Biomolecules 12, nr 7 (2.07.2022): 932. http://dx.doi.org/10.3390/biom12070932.
Pełny tekst źródłaYağci, Mehmet Yavuz, i Muhammed Ali Aydin. "EA-GAT: Event aware graph attention network on cyber-physical systems". Computers in Industry 159-160 (sierpień 2024): 104097. http://dx.doi.org/10.1016/j.compind.2024.104097.
Pełny tekst źródłaZhang, Yuhang, Yaoqun Xu i Yu Zhang. "A Graph Neural Network Node Classification Application Model with Enhanced Node Association". Applied Sciences 13, nr 12 (15.06.2023): 7150. http://dx.doi.org/10.3390/app13127150.
Pełny tekst źródłaYe, Haonan, i 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, nr 1 (25.12.2021): 204. http://dx.doi.org/10.3390/ijerph19010204.
Pełny tekst źródłaLi, Yansheng, Ruixian Chen, Yongjun Zhang, Mi Zhang i Ling Chen. "Multi-Label Remote Sensing Image Scene Classification by Combining a Convolutional Neural Network and a Graph Neural Network". Remote Sensing 12, nr 23 (7.12.2020): 4003. http://dx.doi.org/10.3390/rs12234003.
Pełny tekst źródłaMu, Jichong, Jihong Ouyang, Yachen Yao i Zongxiao Ren. "Span-Prototype Graph Based on Graph Attention Network for Nested Named Entity Recognition". Electronics 12, nr 23 (23.11.2023): 4753. http://dx.doi.org/10.3390/electronics12234753.
Pełny tekst źródłaYang, Xiaohui, Hailong Ma i Miao Wang. "Rumor Detection with Bidirectional Graph Attention Networks". Security and Communication Networks 2022 (18.01.2022): 1–13. http://dx.doi.org/10.1155/2022/4840997.
Pełny tekst źródłaJi, Cunmei, Zhihao Liu, Yutian Wang, Jiancheng Ni i 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, nr 16 (7.08.2021): 8505. http://dx.doi.org/10.3390/ijms22168505.
Pełny tekst źródłaBaul, Sudipto, Khandakar Tanvir Ahmed, Joseph Filipek i Wei Zhang. "omicsGAT: Graph Attention Network for Cancer Subtype Analyses". International Journal of Molecular Sciences 23, nr 18 (6.09.2022): 10220. http://dx.doi.org/10.3390/ijms231810220.
Pełny tekst źródłaWu, Xingping, Qiheng Yuan, Chunlei Zhou, Xiang Chen, Donghai Xuan i Jinwei Song. "Carbon emissions forecasting based on temporal graph transformer-based attentional neural network". Journal of Computational Methods in Sciences and Engineering 24, nr 3 (17.06.2024): 1405–21. http://dx.doi.org/10.3233/jcm-247139.
Pełny tekst źródłaAlothali, Eiman, Motamen Salih, Kadhim Hayawi i Hany Alashwal. "Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots". Applied Sciences 12, nr 16 (13.08.2022): 8117. http://dx.doi.org/10.3390/app12168117.
Pełny tekst źródłaWei, Pengfei, Bi Zeng i Wenxiong Liao. "Joint intent detection and slot filling with wheel-graph attention networks". Journal of Intelligent & Fuzzy Systems 42, nr 3 (2.02.2022): 2409–20. http://dx.doi.org/10.3233/jifs-211674.
Pełny tekst źródłaZhao, Mingxiu, Jing Zhang, Qin Li, Junzheng Yang, Estevao Siga i Tianchi Zhang. "GAT-ABiGRU Based Prediction Model for AUV Trajectory". Applied Sciences 14, nr 10 (15.05.2024): 4184. http://dx.doi.org/10.3390/app14104184.
Pełny tekst źródłaUmair, Muhammad, Iftikhar Alam, Atif Khan, Inayat Khan, Niamat Ullah i Mohammad Yusuf Momand. "N-GPETS: Neural Attention Graph-Based Pretrained Statistical Model for Extractive Text Summarization". Computational Intelligence and Neuroscience 2022 (22.11.2022): 1–14. http://dx.doi.org/10.1155/2022/6241373.
Pełny tekst źródłaChen, Yang, Weibing Wan, Jimi Hu, Yuxuan Wang i Bo Huang. "Complex Causal Extraction of Fusion of Entity Location Sensing and Graph Attention Networks". Information 13, nr 8 (31.07.2022): 364. http://dx.doi.org/10.3390/info13080364.
Pełny tekst źródłaZhou, Hang, Weikun Wang, Jiayun Jin, Zengwei Zheng i Binbin Zhou. "Graph Neural Network for Protein–Protein Interaction Prediction: A Comparative Study". Molecules 27, nr 18 (19.09.2022): 6135. http://dx.doi.org/10.3390/molecules27186135.
Pełny tekst źródłaShao, Yingzhao, Yunsong Li, Li Li, Yuanle Wang, Yuchen Yang, Yueli Ding, Mingming Zhang, Yang Liu i Xiangqiang Gao. "RANet: Relationship Attention for Hyperspectral Anomaly Detection". Remote Sensing 15, nr 23 (30.11.2023): 5570. http://dx.doi.org/10.3390/rs15235570.
Pełny tekst źródłaGao, Yunmeng, Liang Zhao, Jin Du i Junnan Wang. "Spatial-temporal Traffic Flow Prediction Model Based on the GAT and BiGRU". Journal of Physics: Conference Series 2589, nr 1 (1.09.2023): 012024. http://dx.doi.org/10.1088/1742-6596/2589/1/012024.
Pełny tekst źródłaXu, Dawei, Qing Liu, Liehuang Zhu, Zhonghua Tan, Feng Gao i Jian Zhao. "GCNRDM: A Social Network Rumor Detection Method Based on Graph Convolutional Network in Mobile Computing". Wireless Communications and Mobile Computing 2021 (8.10.2021): 1–11. http://dx.doi.org/10.1155/2021/1690669.
Pełny tekst źródłaPeng, Feifei, Wei Lu, Wenxia Tan, Kunlun Qi, Xiaokang Zhang i Quansheng Zhu. "Multi-Output Network Combining GNN and CNN for Remote Sensing Scene Classification". Remote Sensing 14, nr 6 (18.03.2022): 1478. http://dx.doi.org/10.3390/rs14061478.
Pełny tekst źródłaCui, Wei, Yuanjie Hao, Xing Xu, Zhanyun Feng, Huilin Zhao, Cong Xia i Jin Wang. "Remote Sensing Scene Graph and Knowledge Graph Matching with Parallel Walking Algorithm". Remote Sensing 14, nr 19 (29.09.2022): 4872. http://dx.doi.org/10.3390/rs14194872.
Pełny tekst źródłaZhan, Huixin, Kun Zhang, Keyi Lu i 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, nr 13 (26.06.2023): 16380–81. http://dx.doi.org/10.1609/aaai.v37i13.27050.
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