Artículos de revistas sobre el tema "Variational graph auto-Encoder (VGAE)"
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Hui, Binyuan, Pengfei Zhu y Qinghua Hu. "Collaborative Graph Convolutional Networks: Unsupervised Learning Meets Semi-Supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4215–22. http://dx.doi.org/10.1609/aaai.v34i04.5843.
Texto completoDuan, Yuning, Jingdong Jia, Yuhui Jin, Haitian Zhang y Jian Huang. "Expressway Vehicle Trajectory Prediction Based on Fusion Data of Trajectories and Maps from Vehicle Perspective". Applied Sciences 14, n.º 10 (15 de mayo de 2024): 4181. http://dx.doi.org/10.3390/app14104181.
Texto completoChoong, Jun Jin, Xin Liu y Tsuyoshi Murata. "Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization". Entropy 22, n.º 2 (7 de febrero de 2020): 197. http://dx.doi.org/10.3390/e22020197.
Texto completoMa, Weigang, Jing Wang, Chaohui Zhang, Qiao Jia, Lei Zhu, Wenjiang Ji y Zhoukai Wang. "Application of Variational Graph Autoencoder in Traction Control of Energy-Saving Driving for High-Speed Train". Applied Sciences 14, n.º 5 (29 de febrero de 2024): 2037. http://dx.doi.org/10.3390/app14052037.
Texto completoZhang, Jing, Guangli Wu y Shanshan Song. "Video Summarization Generation Based on Graph Structure Reconstruction". Electronics 12, n.º 23 (23 de noviembre de 2023): 4757. http://dx.doi.org/10.3390/electronics12234757.
Texto completoZhang, Ying, Qi Zhang, Yu Zhang y Zhiyuan Zhu. "VGAE-AMF: A Novel Topology Reconstruction Algorithm for Invulnerability of Ocean Wireless Sensor Networks Based on Graph Neural Network". Journal of Marine Science and Engineering 11, n.º 4 (16 de abril de 2023): 843. http://dx.doi.org/10.3390/jmse11040843.
Texto completoPatel, Neel, Nhat Le, Tan Nguyen, Fedaa Najdawi, Sandhya Srinivasan, Adam Stanford-Moore, Deeksha Kartik et al. "Abstract 4912: Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC". Cancer Research 84, n.º 6_Supplement (22 de marzo de 2024): 4912. http://dx.doi.org/10.1158/1538-7445.am2024-4912.
Texto completoShi, Han, Haozheng Fan y James T. Kwok. "Effective Decoding in Graph Auto-Encoder Using Triadic Closure". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 01 (3 de abril de 2020): 906–13. http://dx.doi.org/10.1609/aaai.v34i01.5437.
Texto completoBehrouzi, Tina y Dimitrios Hatzinakos. "Graph variational auto-encoder for deriving EEG-based graph embedding". Pattern Recognition 121 (enero de 2022): 108202. http://dx.doi.org/10.1016/j.patcog.2021.108202.
Texto completoZhan, Junjian, Feng Li, Yang Wang, Daoyu Lin y Guangluan Xu. "Structural Adversarial Variational Auto-Encoder for Attributed Network Embedding". Applied Sciences 11, n.º 5 (7 de marzo de 2021): 2371. http://dx.doi.org/10.3390/app11052371.
Texto completoXie, Luodi, Huimin Huang y Qing Du. "A Co-Embedding Model with Variational Auto-Encoder for Knowledge Graphs". Applied Sciences 12, n.º 2 (12 de enero de 2022): 715. http://dx.doi.org/10.3390/app12020715.
Texto completofathy,, Asmaa Mohamed. "Deep Embedding Data Fusion Scheme Using Variational Graph Auto-Encoder in IoT Environments". International Journal of Advanced Trends in Computer Science and Engineering 9, n.º 4 (25 de agosto de 2020): 4363–72. http://dx.doi.org/10.30534/ijatcse/2020/28942020.
Texto completoZhao, Yuexuan y Jing Huang. "Dirichlet Process Prior for Student’s t Graph Variational Autoencoders". Future Internet 13, n.º 3 (16 de marzo de 2021): 75. http://dx.doi.org/10.3390/fi13030075.
Texto completoYao, Heng, Jihong Guan y Tianying Liu. "Denoising Protein–Protein interaction network via variational graph auto-encoder for protein complex detection". Journal of Bioinformatics and Computational Biology 18, n.º 03 (junio de 2020): 2040010. http://dx.doi.org/10.1142/s0219720020400107.
Texto completoZhou, Qiang, Xinjiang Lu, Jingjing Gu, Zhe Zheng, Bo Jin y Jingbo Zhou. "Explainable Origin-Destination Crowd Flow Interpolation via Variational Multi-Modal Recurrent Graph Auto-Encoder". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 8 (24 de marzo de 2024): 9422–30. http://dx.doi.org/10.1609/aaai.v38i8.28796.
Texto completoKarimi, Mostafa, Arman Hasanzadeh y Yang Shen. "Network-principled deep generative models for designing drug combinations as graph sets". Bioinformatics 36, Supplement_1 (1 de julio de 2020): i445—i454. http://dx.doi.org/10.1093/bioinformatics/btaa317.
Texto completoSu, Hang, Xinzheng Zhang, Yuqing Luo, Ce Zhang, Xichuan Zhou y Peter M. Atkinson. "Nonlocal feature learning based on a variational graph auto-encoder network for small area change detection using SAR imagery". ISPRS Journal of Photogrammetry and Remote Sensing 193 (noviembre de 2022): 137–49. http://dx.doi.org/10.1016/j.isprsjprs.2022.09.006.
Texto completoXu, Lei, Leiming Xia, Shourun Pan y Zhen Li. "Triple Generative Self-Supervised Learning Method for Molecular Property Prediction". International Journal of Molecular Sciences 25, n.º 7 (28 de marzo de 2024): 3794. http://dx.doi.org/10.3390/ijms25073794.
Texto completoDu, Bing, Xiaomu Cheng, Yiping Duan y Huansheng Ning. "fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey". Brain Sciences 12, n.º 2 (7 de febrero de 2022): 228. http://dx.doi.org/10.3390/brainsci12020228.
Texto completoWang, Lei, Zejian Yuan y Badong Chen. "Learning to Generate an Unbiased Scene Graph by Using Attribute-Guided Predicate Features". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 2 (26 de junio de 2023): 2581–89. http://dx.doi.org/10.1609/aaai.v37i2.25356.
Texto completoMao, Cunli, Haoyuan Liang, Zhengtao Yu, Yuxin Huang y Junjun Guo. "A Clustering Method of Case-Involved News by Combining Topic Network and Multi-Head Attention Mechanism". Sensors 21, n.º 22 (11 de noviembre de 2021): 7501. http://dx.doi.org/10.3390/s21227501.
Texto completoZhao, Mingle, Dingfu Zhou, Xibin Song, Xiuwan Chen y Liangjun Zhang. "DiT-SLAM: Real-Time Dense Visual-Inertial SLAM with Implicit Depth Representation and Tightly-Coupled Graph Optimization". Sensors 22, n.º 9 (28 de abril de 2022): 3389. http://dx.doi.org/10.3390/s22093389.
Texto completoLi, Peng, Shufang Guo, Chenghao Zhang, Mosharaf Md Parvej y Jing Zhang. "A Construction Method for a Dynamic Weighted Protein Network Using Multi-Level Embedding". Applied Sciences 14, n.º 10 (11 de mayo de 2024): 4090. http://dx.doi.org/10.3390/app14104090.
Texto completoZhu, Guixiang, Jie Cao, Lei Chen, Youquan Wang, Zhan Bu, Shuxin Yang, Jianqing Wu y Zhiping Wang. "A Multi-task Graph Neural Network with Variational Graph Auto-Encoders for Session-based Travel Packages Recommendation". ACM Transactions on the Web, febrero de 2023. http://dx.doi.org/10.1145/3577032.
Texto completoLi, Dongjie, Dong Li y Guang Lian. "Variational Graph Autoencoder with Adversarial Mutual Information Learning for Network Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22 de agosto de 2022. http://dx.doi.org/10.1145/3555809.
Texto completoYuan, Wei, Shiyu Zhao, Li Wang, Lijia Cai y Yong Zhang. "Online course evaluation model based on graph auto-encoder". Intelligent Data Analysis, 21 de marzo de 2024, 1–23. http://dx.doi.org/10.3233/ida-230557.
Texto completoLi, Dongjie, Dong Li y Guang Lian. "Variational Graph Autoencoder with Mutual Information Maximization for Graph Representations Learning". International Journal of Pattern Recognition and Artificial Intelligence, 8 de junio de 2022. http://dx.doi.org/10.1142/s0218001422520127.
Texto completoIwata, Hiroaki, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima y Yasushi Okuno. "VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search". Journal of Chemical Information and Modeling, 22 de noviembre de 2023. http://dx.doi.org/10.1021/acs.jcim.3c01220.
Texto completoLiu, Zhi, Yang Chen, Feng Xia, Jixin Bian, Bing Zhu, Guojiang Shen y Xiangjie Kong. "TAP: Traffic Accident Profiling via Multi-task Spatio-Temporal Graph Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22 de septiembre de 2022. http://dx.doi.org/10.1145/3564594.
Texto completoLi, Bo, Chen Peng, Zeran You, Xiaolong Zhang y Shihua Zhang. "Single-cell RNA-sequencing data clustering using variational graph attention auto-encoder with self-supervised leaning". Briefings in Bioinformatics 24, n.º 6 (22 de septiembre de 2023). http://dx.doi.org/10.1093/bib/bbad383.
Texto completoDuy Nguyen, Viet Thanh y Truong Son Hy. "Multimodal pretraining for unsupervised protein representation learning". Biology Methods and Protocols, 18 de junio de 2024. http://dx.doi.org/10.1093/biomethods/bpae043.
Texto completoYi, Jing y Zhenzhong Chen. "Multi-modal Variational Graph Auto-encoder for Recommendation Systems". IEEE Transactions on Multimedia, 2021, 1. http://dx.doi.org/10.1109/tmm.2021.3111487.
Texto completoMrabah, Nairouz, Mohamed Bouguessa y Riadh Ksantini. "A contrastive variational graph auto-encoder for node clustering". Pattern Recognition, diciembre de 2023, 110209. http://dx.doi.org/10.1016/j.patcog.2023.110209.
Texto completoZhang, Yi, Yiwen Zhang, Dengcheng Yan, Shuiguang Deng y Yun Yang. "Revisiting Graph-based Recommender Systems from the Perspective of Variational Auto-Encoder". ACM Transactions on Information Systems, diciembre de 2022. http://dx.doi.org/10.1145/3573385.
Texto completoZhou, Xin y Chunyan Miao. "Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation With Interpretability". IEEE Transactions on Multimedia, 2024, 1–13. http://dx.doi.org/10.1109/tmm.2024.3369875.
Texto completoYi, Jing, Xubin Ren y Zhenzhong Chen. "Multi-Auxiliary Augmented Collaborative Variational Auto-encoder for Tag Recommendation". ACM Transactions on Information Systems, 31 de enero de 2023. http://dx.doi.org/10.1145/3578932.
Texto completoChen, Han, Hanchen Wang, Hongmei Chen, Ying Zhang, Wenjie Zhang y Xuemin Lin. "Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions". IEEE Transactions on Knowledge and Data Engineering, 2023, 1–14. http://dx.doi.org/10.1109/tkde.2023.3298490.
Texto completoZhu, Yuan, Feng Zhang, Shihua Zhang y Ming Yi. "Predicting latent lncRNA and cancer metastatic event associations via variational graph auto-encoder". Methods, enero de 2023. http://dx.doi.org/10.1016/j.ymeth.2023.01.006.
Texto completoGervits, Asia y Roded Sharan. "Predicting genetic interactions, cell line dependencies and drug sensitivities with variational graph auto-encoder". Frontiers in Bioinformatics 2 (2 de diciembre de 2022). http://dx.doi.org/10.3389/fbinf.2022.1025783.
Texto completoDing, Yulian, Xiujuan Lei, Bo Liao y Fangxiang Wu. "Predicting miRNA-Disease Associations Based on Multi-View Variational Graph Auto-Encoder with Matrix Factorization". IEEE Journal of Biomedical and Health Informatics, 2021, 1. http://dx.doi.org/10.1109/jbhi.2021.3088342.
Texto completoFu, Yao, Runtao Yang y Lina Zhang. "Association prediction of CircRNAs and diseases using multi-homogeneous graphs and variational graph auto-encoder". Computers in Biology and Medicine, noviembre de 2022, 106289. http://dx.doi.org/10.1016/j.compbiomed.2022.106289.
Texto completoAftab, Rukhma, Yan Qiang, Juanjuan Zhao, Zia Urrehman y Zijuan Zhao. "Graph Neural Network for representation learning of lung cancer". BMC Cancer 23, n.º 1 (26 de octubre de 2023). http://dx.doi.org/10.1186/s12885-023-11516-8.
Texto completoNgo, Nhat Khang y Truong Son Hy. "Multimodal Protein Representation Learning and Target-aware Variational Auto-encoders for Protein-binding Ligand Generation". Machine Learning: Science and Technology, 15 de abril de 2024. http://dx.doi.org/10.1088/2632-2153/ad3ee4.
Texto completoZhang, Yihao, Yuhao Wang, Wei Zhou, Pengxiang Lan, Haoran Xiang, Junlin Zhu y Meng Yuan. "Conversational recommender based on graph sparsification and multi-hop attention". Intelligent Data Analysis, 14 de septiembre de 2023, 1–21. http://dx.doi.org/10.3233/ida-230148.
Texto completoLi, Yunyi, Yongjing Hao, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng y Xiaofang Zhou. "Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation". ACM Transactions on Knowledge Discovery from Data, 6 de febrero de 2023. http://dx.doi.org/10.1145/3577928.
Texto completoPeng, Lihong, Liangliang Huang, Qiongli Su, Geng Tian, Min Chen y Guosheng Han. "LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine". Briefings in Bioinformatics 25, n.º 1 (22 de noviembre de 2023). http://dx.doi.org/10.1093/bib/bbad466.
Texto completoBhavna, Km, Azman Akhter, Romi Banerjee y Dipanjan Roy. "Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage". Frontiers in Neuroinformatics 18 (28 de junio de 2024). http://dx.doi.org/10.3389/fninf.2024.1392661.
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