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检索条件"主题词=Variational autoencoder"
1569 条 记 录,以下是961-970 订阅
Cross-Situational Word Learning in Disentangled Latent Space
Cross-Situational Word Learning in Disentangled Latent Space
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IEEE International Conference on Development and Learning (ICDL)
作者: Matsui, Yuta Taniguchi, Akira Hagiwara, Yoshinobu Taniguchi, Tadahiro Ritsumeikan Univ Grad Sch Informat Sci & Engn Kusatsu Shiga Japan Ritsumeikan Univ Coll Informat Sci & Engn Kusatsu Shiga Japan Ritsumeikan Univ Res Org Sci & Technol Kusatsu Shiga Japan
Cross-situational word learning (CSL) is a fast and efficient method for humans to acquire word meanings. Many studies have replicated human CSL using computational models. Among these, cross-situational learning with... 详细信息
来源: 评论
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids
Latent Neural ODE for Integrating Multi-timescale measuremen...
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IEEE-Power-and-Energy-Society Innovative Smart Grid Technologies Conference (ISGT)
作者: Dahale, Shweta Munikoti, Sai Natarajan, Balasubramaniam Yang, Rui Kansas State Univ Elect & Comp Engn Manhattan KS 66506 USA Natl Renewable Energy Lab NREL Golden CO USA Natl Renewable Energy Lab NREL Sensing & Predict Analyt Grp Power Syst Engn Ctr Golden CO 80401 USA Kansas State Univ Elect & Comp Engn Manhattan KS 66506 USA
Under a smart grid paradigm, there has been an increase in sensor installations to enhance situational awareness. The measurements from these sensors can be leveraged for real-time monitoring, control, and protection.... 详细信息
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WEAKLY SUPERVISED DISENTANGLEMENT WITH TRIPLET NETWORK  30
WEAKLY SUPERVISED DISENTANGLEMENT WITH TRIPLET NETWORK
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30th IEEE International Conference on Image Processing (ICIP)
作者: Coutinho, Pedro C. C. C. C. Berthoumieu, Yannick Donias, Marc Guillon, Sebastien TotalEnergies OneTech Paris France Univ Bordeaux CNRS Bordeaux INP IMSUMR 5218 Bordeaux France
variational autoencoders have gained considerable attention due to their capacity of encoding high dimensional data into a lower dimensional latent space. In this context, several methods have been proposed with the o... 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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variational Manifold Learning From Incomplete Data: Application to Multislice Dynamic MRI
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IEEE TRANSACTIONS ON MEDICAL IMAGING 2022年 第12期41卷 3552-3561页
作者: Zou, Qing Ahmed, Abdul Haseeb Nagpal, Prashant Priya, Sarv Schulte, Rolf F. Jacob, Mathews Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA Philips Healthcare Rochester MN 55311 USA Univ Wisconsin Madison Dept Radiol Madison WI 53706 USA Univ Iowa Dept Radiol Iowa City IA 52242 USA Gen Elect Healthcare D-80807 Munich Germany
Current deep learning-based manifold learning algorithms such as the variational autoencoder (VAE) require fully sampled data to learn the probability density of real-world datasets. However, fully sampled data is oft... 详细信息
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An Auto-Encoder with Genetic Algorithm for High Dimensional Data: Towards Accurate and Interpretable Outlier Detection
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ALGORITHMS 2022年 第11期15卷 429-429页
作者: Li, Jiamu Zhang, Ji Bah, Mohamed Jaward Wang, Jian Zhu, Youwen Yang, Gaoming Li, Lingling Zhang, Kexin Nanjing Univ Aeronaut & Astronaut Sch Comp Sci & Technol Nanjing 210016 Peoples R China Univ Southern Queensland Sch Math Phys & Comp Toowoomba Qld 4350 Australia Zhejiang Lab Big Data Intelligence Res Ctr Hangzhou 311121 Peoples R China Anhui Univ Sci & Technol Sch Comp Sci & Engn Huainan 243002 Peoples R China Zhengzhou Univ Aeronaut Sch Intelligent Engn Zhengzhou 450046 Peoples R China
When dealing with high-dimensional data, such as in biometric, e-commerce, or industrial applications, it is extremely hard to capture the abnormalities in full space due to the curse of dimensionality. Furthermore, i... 详细信息
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The road from MLE to EM to VAE: A brief tutorial
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AI OPEN 2022年 3卷 29-34页
作者: Ding, Ming Tsinghua Univ Beijing Peoples R China
variational Auto -Encoders (VAEs) have emerged as one of the most popular genres of generative models , which are learned to characterize the data distribution. The classic Expectation Maximization (EM) algorithm aims... 详细信息
来源: 评论
Semi-supervised Cavitation Detection for Centrifugal Pumps
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TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A 2022年 第2期46卷 153-162页
作者: Yoo, Donghwi Choi, Minseok Kim, Chungeon Oh, Hyunseok Gwangju Inst Sci & Technol Sch Mech Engn Gwangju South Korea
Cavitation is a dominant failure mode that accelerates the wear and deterioration of pumps. Cavitation can lead to pump malfunction and, eventually, catastrophic failure of the whole system. Therefore, it is important... 详细信息
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Cost-Sensitive variational Autoencoding Classifier for Imbalanced Data Classification
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ALGORITHMS 2022年 第5期15卷 139-139页
作者: Liu, Fen Qian, Quan Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Shanghai Univ Mat Genome Inst Shanghai 200444 Peoples R China Zhejiang Lab Hangzhou 311100 Peoples R China
Classification is among the core tasks in machine learning. Existing classification algorithms are typically based on the assumption of at least roughly balanced data classes. When performing tasks involving imbalance... 详细信息
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