Artykuły w czasopismach na temat „Variational graph auto-Encoder (VGAE)”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 47 najlepszych artykułów w czasopismach naukowych na temat „Variational graph auto-Encoder (VGAE)”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Hui, Binyuan, Pengfei Zhu i Qinghua Hu. "Collaborative Graph Convolutional Networks: Unsupervised Learning Meets Semi-Supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 4215–22. http://dx.doi.org/10.1609/aaai.v34i04.5843.
Pełny tekst źródłaDuan, Yuning, Jingdong Jia, Yuhui Jin, Haitian Zhang i Jian Huang. "Expressway Vehicle Trajectory Prediction Based on Fusion Data of Trajectories and Maps from Vehicle Perspective". Applied Sciences 14, nr 10 (15.05.2024): 4181. http://dx.doi.org/10.3390/app14104181.
Pełny tekst źródłaChoong, Jun Jin, Xin Liu i Tsuyoshi Murata. "Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization". Entropy 22, nr 2 (7.02.2020): 197. http://dx.doi.org/10.3390/e22020197.
Pełny tekst źródłaMa, Weigang, Jing Wang, Chaohui Zhang, Qiao Jia, Lei Zhu, Wenjiang Ji i Zhoukai Wang. "Application of Variational Graph Autoencoder in Traction Control of Energy-Saving Driving for High-Speed Train". Applied Sciences 14, nr 5 (29.02.2024): 2037. http://dx.doi.org/10.3390/app14052037.
Pełny tekst źródłaZhang, Jing, Guangli Wu i Shanshan Song. "Video Summarization Generation Based on Graph Structure Reconstruction". Electronics 12, nr 23 (23.11.2023): 4757. http://dx.doi.org/10.3390/electronics12234757.
Pełny tekst źródłaZhang, Ying, Qi Zhang, Yu Zhang i 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, nr 4 (16.04.2023): 843. http://dx.doi.org/10.3390/jmse11040843.
Pełny tekst źródłaPatel, Neel, Nhat Le, Tan Nguyen, Fedaa Najdawi, Sandhya Srinivasan, Adam Stanford-Moore, Deeksha Kartik i in. "Abstract 4912: Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC". Cancer Research 84, nr 6_Supplement (22.03.2024): 4912. http://dx.doi.org/10.1158/1538-7445.am2024-4912.
Pełny tekst źródłaShi, Han, Haozheng Fan i James T. Kwok. "Effective Decoding in Graph Auto-Encoder Using Triadic Closure". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 01 (3.04.2020): 906–13. http://dx.doi.org/10.1609/aaai.v34i01.5437.
Pełny tekst źródłaBehrouzi, Tina, i Dimitrios Hatzinakos. "Graph variational auto-encoder for deriving EEG-based graph embedding". Pattern Recognition 121 (styczeń 2022): 108202. http://dx.doi.org/10.1016/j.patcog.2021.108202.
Pełny tekst źródłaZhan, Junjian, Feng Li, Yang Wang, Daoyu Lin i Guangluan Xu. "Structural Adversarial Variational Auto-Encoder for Attributed Network Embedding". Applied Sciences 11, nr 5 (7.03.2021): 2371. http://dx.doi.org/10.3390/app11052371.
Pełny tekst źródłaXie, Luodi, Huimin Huang i Qing Du. "A Co-Embedding Model with Variational Auto-Encoder for Knowledge Graphs". Applied Sciences 12, nr 2 (12.01.2022): 715. http://dx.doi.org/10.3390/app12020715.
Pełny tekst źródłafathy,, 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, nr 4 (25.08.2020): 4363–72. http://dx.doi.org/10.30534/ijatcse/2020/28942020.
Pełny tekst źródłaZhao, Yuexuan, i Jing Huang. "Dirichlet Process Prior for Student’s t Graph Variational Autoencoders". Future Internet 13, nr 3 (16.03.2021): 75. http://dx.doi.org/10.3390/fi13030075.
Pełny tekst źródłaYao, Heng, Jihong Guan i Tianying Liu. "Denoising Protein–Protein interaction network via variational graph auto-encoder for protein complex detection". Journal of Bioinformatics and Computational Biology 18, nr 03 (czerwiec 2020): 2040010. http://dx.doi.org/10.1142/s0219720020400107.
Pełny tekst źródłaZhou, Qiang, Xinjiang Lu, Jingjing Gu, Zhe Zheng, Bo Jin i 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, nr 8 (24.03.2024): 9422–30. http://dx.doi.org/10.1609/aaai.v38i8.28796.
Pełny tekst źródłaKarimi, Mostafa, Arman Hasanzadeh i Yang Shen. "Network-principled deep generative models for designing drug combinations as graph sets". Bioinformatics 36, Supplement_1 (1.07.2020): i445—i454. http://dx.doi.org/10.1093/bioinformatics/btaa317.
Pełny tekst źródłaSu, Hang, Xinzheng Zhang, Yuqing Luo, Ce Zhang, Xichuan Zhou i 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 (listopad 2022): 137–49. http://dx.doi.org/10.1016/j.isprsjprs.2022.09.006.
Pełny tekst źródłaXu, Lei, Leiming Xia, Shourun Pan i Zhen Li. "Triple Generative Self-Supervised Learning Method for Molecular Property Prediction". International Journal of Molecular Sciences 25, nr 7 (28.03.2024): 3794. http://dx.doi.org/10.3390/ijms25073794.
Pełny tekst źródłaDu, Bing, Xiaomu Cheng, Yiping Duan i Huansheng Ning. "fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey". Brain Sciences 12, nr 2 (7.02.2022): 228. http://dx.doi.org/10.3390/brainsci12020228.
Pełny tekst źródłaWang, Lei, Zejian Yuan i Badong Chen. "Learning to Generate an Unbiased Scene Graph by Using Attribute-Guided Predicate Features". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 2 (26.06.2023): 2581–89. http://dx.doi.org/10.1609/aaai.v37i2.25356.
Pełny tekst źródłaMao, Cunli, Haoyuan Liang, Zhengtao Yu, Yuxin Huang i Junjun Guo. "A Clustering Method of Case-Involved News by Combining Topic Network and Multi-Head Attention Mechanism". Sensors 21, nr 22 (11.11.2021): 7501. http://dx.doi.org/10.3390/s21227501.
Pełny tekst źródłaZhao, Mingle, Dingfu Zhou, Xibin Song, Xiuwan Chen i Liangjun Zhang. "DiT-SLAM: Real-Time Dense Visual-Inertial SLAM with Implicit Depth Representation and Tightly-Coupled Graph Optimization". Sensors 22, nr 9 (28.04.2022): 3389. http://dx.doi.org/10.3390/s22093389.
Pełny tekst źródłaLi, Peng, Shufang Guo, Chenghao Zhang, Mosharaf Md Parvej i Jing Zhang. "A Construction Method for a Dynamic Weighted Protein Network Using Multi-Level Embedding". Applied Sciences 14, nr 10 (11.05.2024): 4090. http://dx.doi.org/10.3390/app14104090.
Pełny tekst źródłaZhu, Guixiang, Jie Cao, Lei Chen, Youquan Wang, Zhan Bu, Shuxin Yang, Jianqing Wu i Zhiping Wang. "A Multi-task Graph Neural Network with Variational Graph Auto-Encoders for Session-based Travel Packages Recommendation". ACM Transactions on the Web, luty 2023. http://dx.doi.org/10.1145/3577032.
Pełny tekst źródłaLi, Dongjie, Dong Li i Guang Lian. "Variational Graph Autoencoder with Adversarial Mutual Information Learning for Network Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22.08.2022. http://dx.doi.org/10.1145/3555809.
Pełny tekst źródłaYuan, Wei, Shiyu Zhao, Li Wang, Lijia Cai i Yong Zhang. "Online course evaluation model based on graph auto-encoder". Intelligent Data Analysis, 21.03.2024, 1–23. http://dx.doi.org/10.3233/ida-230557.
Pełny tekst źródłaLi, Dongjie, Dong Li i Guang Lian. "Variational Graph Autoencoder with Mutual Information Maximization for Graph Representations Learning". International Journal of Pattern Recognition and Artificial Intelligence, 8.06.2022. http://dx.doi.org/10.1142/s0218001422520127.
Pełny tekst źródłaIwata, Hiroaki, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima i 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, 22.11.2023. http://dx.doi.org/10.1021/acs.jcim.3c01220.
Pełny tekst źródłaLiu, Zhi, Yang Chen, Feng Xia, Jixin Bian, Bing Zhu, Guojiang Shen i Xiangjie Kong. "TAP: Traffic Accident Profiling via Multi-task Spatio-Temporal Graph Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22.09.2022. http://dx.doi.org/10.1145/3564594.
Pełny tekst źródłaLi, Bo, Chen Peng, Zeran You, Xiaolong Zhang i Shihua Zhang. "Single-cell RNA-sequencing data clustering using variational graph attention auto-encoder with self-supervised leaning". Briefings in Bioinformatics 24, nr 6 (22.09.2023). http://dx.doi.org/10.1093/bib/bbad383.
Pełny tekst źródłaDuy Nguyen, Viet Thanh, i Truong Son Hy. "Multimodal pretraining for unsupervised protein representation learning". Biology Methods and Protocols, 18.06.2024. http://dx.doi.org/10.1093/biomethods/bpae043.
Pełny tekst źródłaYi, Jing, i 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.
Pełny tekst źródłaMrabah, Nairouz, Mohamed Bouguessa i Riadh Ksantini. "A contrastive variational graph auto-encoder for node clustering". Pattern Recognition, grudzień 2023, 110209. http://dx.doi.org/10.1016/j.patcog.2023.110209.
Pełny tekst źródłaZhang, Yi, Yiwen Zhang, Dengcheng Yan, Shuiguang Deng i Yun Yang. "Revisiting Graph-based Recommender Systems from the Perspective of Variational Auto-Encoder". ACM Transactions on Information Systems, grudzień 2022. http://dx.doi.org/10.1145/3573385.
Pełny tekst źródłaZhou, Xin, i 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.
Pełny tekst źródłaYi, Jing, Xubin Ren i Zhenzhong Chen. "Multi-Auxiliary Augmented Collaborative Variational Auto-encoder for Tag Recommendation". ACM Transactions on Information Systems, 31.01.2023. http://dx.doi.org/10.1145/3578932.
Pełny tekst źródłaChen, Han, Hanchen Wang, Hongmei Chen, Ying Zhang, Wenjie Zhang i 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.
Pełny tekst źródłaZhu, Yuan, Feng Zhang, Shihua Zhang i Ming Yi. "Predicting latent lncRNA and cancer metastatic event associations via variational graph auto-encoder". Methods, styczeń 2023. http://dx.doi.org/10.1016/j.ymeth.2023.01.006.
Pełny tekst źródłaGervits, Asia, i Roded Sharan. "Predicting genetic interactions, cell line dependencies and drug sensitivities with variational graph auto-encoder". Frontiers in Bioinformatics 2 (2.12.2022). http://dx.doi.org/10.3389/fbinf.2022.1025783.
Pełny tekst źródłaDing, Yulian, Xiujuan Lei, Bo Liao i 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.
Pełny tekst źródłaFu, Yao, Runtao Yang i Lina Zhang. "Association prediction of CircRNAs and diseases using multi-homogeneous graphs and variational graph auto-encoder". Computers in Biology and Medicine, listopad 2022, 106289. http://dx.doi.org/10.1016/j.compbiomed.2022.106289.
Pełny tekst źródłaAftab, Rukhma, Yan Qiang, Juanjuan Zhao, Zia Urrehman i Zijuan Zhao. "Graph Neural Network for representation learning of lung cancer". BMC Cancer 23, nr 1 (26.10.2023). http://dx.doi.org/10.1186/s12885-023-11516-8.
Pełny tekst źródłaNgo, Nhat Khang, i Truong Son Hy. "Multimodal Protein Representation Learning and Target-aware Variational Auto-encoders for Protein-binding Ligand Generation". Machine Learning: Science and Technology, 15.04.2024. http://dx.doi.org/10.1088/2632-2153/ad3ee4.
Pełny tekst źródłaZhang, Yihao, Yuhao Wang, Wei Zhou, Pengxiang Lan, Haoran Xiang, Junlin Zhu i Meng Yuan. "Conversational recommender based on graph sparsification and multi-hop attention". Intelligent Data Analysis, 14.09.2023, 1–21. http://dx.doi.org/10.3233/ida-230148.
Pełny tekst źródłaLi, Yunyi, Yongjing Hao, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng i Xiaofang Zhou. "Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation". ACM Transactions on Knowledge Discovery from Data, 6.02.2023. http://dx.doi.org/10.1145/3577928.
Pełny tekst źródłaPeng, Lihong, Liangliang Huang, Qiongli Su, Geng Tian, Min Chen i 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, nr 1 (22.11.2023). http://dx.doi.org/10.1093/bib/bbad466.
Pełny tekst źródłaBhavna, Km, Azman Akhter, Romi Banerjee i 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 (28.06.2024). http://dx.doi.org/10.3389/fninf.2024.1392661.
Pełny tekst źródła