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检索条件"主题词=Variational autoencoder"
1534 条 记 录,以下是1291-1300 订阅
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Anomaly detection for data accountability of Mars telemetry data
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EXPERT SYSTEMS WITH APPLICATIONS 2022年 189卷 116060-116060页
作者: Lakhmiri, Dounia Alimo, Ryan Le Digabel, Sebastien GERAD Montreal PQ Canada Polytech Montreal Montreal PQ Canada Jet Prop Lab Pasadena CA USA CALTECH Pasadena CA 91125 USA
The Mars Curiosity rover is frequently sending engineering and science data that goes through a pipeline of systems before reaching its final destination at the mission operations center making it prone to volume loss... 详细信息
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Spatio-Temporal Hourly and Daily Ozone Forecasting in China Using a Hybrid Machine Learning Model: autoencoder and Generative Adversarial Networks
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JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2022年 第3期14卷
作者: Cheng, Meiling Fang, Fangxin Navon, Ionel M. Zheng, Jie Tang, Xiao Zhu, Jiang Pain, Christopher Imperial Coll London Dept Earth Sci & Engn Appl Modelling & Computat Grp London England Florida State Univ Dept Sci Comp Tallahassee FL 32306 USA Chinese Acad Sci Ctr Excellence Reg Atmospher Environm Inst Urban Environm Xiamen Peoples R China Chinese Acad Sci Int Ctr Climate & Environm Sci Inst Atmospher Phys Beijing Peoples R China
Efficient and accurate real-time forecasting of national spatial ozone distribution is critical to the provision of effective early warning. Traditional numerical air quality models require a high computational cost a... 详细信息
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Regularizing variational autoencoders for Molecular Graph Generation  1
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26th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific-Neural-Network-Society (APNNS)
作者: Li, Xin Lyu, Xiaoqing Zhang, Hao Hu, Keqi Tang, Zhi Peking Univ Beijing Peoples R China Beijing Inst Technol Beijing Peoples R China China Univ Min & Technol Beijing Peoples R China
Deep generative models for graphs are promising for being able to sidestep expensive search procedures in the huge space of chemical compounds. However, incorporating complex and non-differentiable property metrics in... 详细信息
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Deep generative modelling of aircraft trajectories in terminal maneuvering areas
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MACHINE LEARNING WITH APPLICATIONS 2023年 11卷
作者: Krauth, Timothe Lafage, Adrien Morio, Jerome Olive, Xavier Waltert, Manuel Zurich Univ Appl Sci Ctr Aviat Winterthur Switzerland Univ Toulouse ONERA DTIS F-31055 Toulouse France Tech str 71 CH-8400 Winterthur Switzerland
Airspace design is subject to a multitude of constraints, which are mainly driven by the concern to keep the risk of mid-air collision below a target level of safety. For that purpose, Monte Carlo simulation methods c... 详细信息
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Near-Real-Time Identification of Seismic Damage Using Unsupervised Deep Neural Network
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JOURNAL OF ENGINEERING MECHANICS 2022年 第3期148卷
作者: Kim, Minkyu Song, Junho Seoul Natl Univ Dept Civil & Environm Engn Seoul 08826 South Korea
Prompt identification of structural damage is essential for effective postdisaster responses. To this end, this paper proposes a deep neural network (DNN)-based framework to identify seismic damage based on structural... 详细信息
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Handling information loss of graph convolutional networks in collaborative filtering
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INFORMATION SYSTEMS 2022年 109卷
作者: Xiong, Xin Li, XunKai Hu, YouPeng Wu, YiXuan Yin, Jian Nanjing Univ Sch Artificial Intelligence 163 Xianlin Ave Nanjing Jiangsu Peoples R China Shandong Univ Sch Mech Elect & Informat Engn 180 Wenhua West Rd Weihai Shandong Peoples R China Zhejiang Univ Polytech Inst 269 Shixiang Rd Hangzhou Zhejiang Peoples R China
Collaborative filtering (CF) methods based on graph convolutional network (GCN) and autoencoder (AE) achieve outstanding performance. But the GCN-based CF methods suffer from information loss problems, which are cause... 详细信息
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Graph Regularized variational Ladder Networks for Semi-Supervised Learning
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IEEE ACCESS 2020年 8卷 206280-206288页
作者: Hu, Cong Song, Xiao-Ning Jiangnan Univ Sch Artificial Intelligence & Comp Sci Wuxi 214122 Jiangsu Peoples R China Jiangnan Univ Jiangsu Prov Engn Lab Pattern Recognit & Computat Wuxi 214122 Jiangsu Peoples R China Minjiang Univ Fujian Prov Key Lab Informat Proc & Intelligent C Fuzhou 350121 Peoples R China
To tackle the problem of semi-supervised learning (SSL), we propose a new autoencoder-based deep model. Ladder networks (LN) is an autoencoder-based method for representation learning which has been successfully appli... 详细信息
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MDMaaS: Medical-Assisted Diagnosis Model as a Service With Artificial Intelligence and Trust
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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2020年 第3期16卷 2102-2114页
作者: Guo, Kehua Ren, Sheng Bhuiyan, Md Zakirul Alam Li, Ting Liu, Dengchao Liang, Zhonghe Chen, Xiang Cent South Univ Sch Engn & Comp Sci Changsha 410083 Peoples R China Fordham Univ Dept Comp & Informat Sci Bronx NY 10458 USA Cent South Univ Dept Dermatol Xiangya Hosp Changsha 410083 Peoples R China
Artificial intelligence has achieved great success in the field of medical-assisted diagnosis, and a deep learning technology plays a very important role in medical image recognition. However, it usually takes medical... 详细信息
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variational Domain Adversarial Learning With Mutual Information Maximization for Speaker Verification
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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2020年 28卷 2013-2024页
作者: Tu, Youzhi Mak, Man-Wai Chien, Jen-Tzung Hong Kong Polytech Univ Dept Elect & Informat Engn Hong Kong Peoples R China Natl Chiao Tung Univ Dept Elect & Comp Engn Hsinchu 30010 Taiwan
Domain mismatch is a common problem in speaker verification (SV) and often causes performance degradation. For the system relying on the Gaussian PLDA backend to suppress the channel variability, the performance would... 详细信息
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Convolutional auto encoders for sentence representation generation
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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2020年 第2期28卷 1135-+页
作者: Ceylan, Ali Mert Aytac, Vecdi Ege Univ Fac Engn Dept Comp Engn Izmir Turkey
In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give... 详细信息
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