Výsledky vyhledávání - Distributed variational autoencoder

DistVAE: Distributed Variational Autoencoder for sequential recommendation Autor Li, Li, Xiahou, Jianbing, Lin, Fan, Su, Songzhi

“… Recently, the generative methods based on Variational Autoencoder (VAE) have shown promising performance in modeling temporal dependencies among items in user sequences…”
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Attribute-relevant distributed variational autoencoder integrated with LSTM for dynamic industrial soft sensing Autor He, Yan-Lin, Li, Xing-Yuan, Ma, Jia-Hui, Zhu, Qun-Xiong, Lu, Shan

“… distributed variational autoencoder (AR-DVAE) is first proposed to effectively extract features from input variables with different correlations…”
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Distributed temporal–spatial neighbourhood enhanced variational autoencoder for multiunit industrial plant‐wide process monitoring Autor Yao, Zongyu, Jiang, Qingchao, Gu, Xingsheng, Pan, Chunjian

“… In this paper, a novel distributed temporal–spatial neighbourhood enhanced variational autoencoder (DTS‐VAE…”
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A novel distributed CVRAE-based spatio-temporal process monitoring method with its application Autor Tang, Peng, Peng, Kaixiang, Chen, Zhiwen, Dong, Jie

“… Then, a distributed conditional variational recurrent autoencoder (CVRAE)-based process monitoring method is proposed to build the local latent variable model of each subsystem using relevant dynamic features extracted from the previous subsystem…”
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Anomaly Detection in Distributed Systems via Variational Autoencoders Autor Qian, Yun, Ying, Shi, Wang, Bingming

“… In this paper, we propose VeLog, an automatic anomaly detection method based on variational autoencoders (VAEs…”
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Variational Autoencoder Based Distributed Unsupervised Meta-learning Framework Autor Wang, Zhenzhen, He, Bing, Kang, Weijie, Zhang, Xianyang

“…) that is founded on the Variational Autoencoder (VAE) and a fusion strategy. Each agent optimizes the variational parameters on local data and fuses its neighboring parameters to acquire a global variational model…”
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Feasibility of a Specklegram-Based Quasi-Distributed Temperature Sensor With Principal Component Analysis and Variational Autoencoder Autor Yue, Shichao, Lu, Huizhen, Li, Boyi, Che, Zifan

“…) and a hybrid model that combines principal component analysis and variational autoencoder (PCAVAE). The proposed MMF optical sensor demonstrates strong performance…”
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Distributed process monitoring based on Kantorovich distance-multiblock variational autoencoder and Bayesian inference Autor Yao, Zongyu, Jiang, Qingchao, Gu, Xingsheng

“… Therefore, the distributed modeling process monitoring method is effective. A novel distributed monitoring scheme utilizing the Kantorovich distance-multiblock variational autoencoder (KD-MBVAE) is introduced…”
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A Novel Distributed Fault Detection Approach Based on the Variational Autoencoder Model Autor Huang, Chenghong, Chai, Yi, Zhu, Zheren, Liu, Bowen, Tang, Qiu

“… Variational autoencoder (VAE) is not only a popular deep generative model but also has a powerful nonlinear feature extraction capability…”
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Network Traffic Anomaly Detection Using t-Distributed Stochastic Neighbor Embedding and Variational Autoencoder Approach Autor P, Chandra Sekar, G U, Vasanthakumar, Adnan, Myasar M., Soujanya, Thota, Ai Sadi, Hafidh I.

“… This paper presents a t-Distributed Stochastic Neighbor Embedding and Variational Autoencoder (t-SNE-VAE…”
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A demonstration of unsupervised machine learning in species delimitation Autor Derkarabetian, Shahan, Castillo, Stephanie, Koo, Peter K., Ovchinnikov, Sergey, Hedin, Marshal

“…[Display omitted] •Unsupervised machine learning methods correctly identify species-level divergences.•Multiple empirical and simulated datasets demonstrate…”
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Federated Variational Autoencoders for Unsupervised Anomaly Detection in Distributed 5G Networks Autor Sheikhi, Saeid, Ghaffari, Amirhossein, Amiri, Aref, Loven, Lauri

“… This paper presents a federated learning framework based on Variational Autoencoders (VAEs) for distributed anomaly detection in 5G network environments…”
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Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization Autor Hagad, Juan, Kimura, Tsukasa, Fukui, Ken-ichi, Numao, Masayuki

“… distributed subject-independent feature embeddings. Variational autoencoders (VAEs) at the input level allow the lower feature layers of the model to be trained on both labeled and unlabeled samples, maximizing the use of the limited data resources…”
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Holographic-(V)AE: An end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space Autor Visani, Gian Marco, Pun, Michael N., Angaji, Arman, Nourmohammad, Armita

“…], a fully end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space, suitable for unsupervised learning and generation of data distributed around a specified origin in 3D. H-(V…”
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Secure Selective Distributed Learning of Autoencoders in Automl Applications Autor Fomicheva, S.G., Zhemelev, G.A.

“…Protocol of selective learning for a variational autoencoder with automatic architecture optimization is proposed, and the effectiveness of distributed learning for latent variables of variational…”
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Learning Latent Distribution for Distinguishing Network Traffic in Intrusion Detection System Autor Vu, Ly, Cao, Van Loi, Nguyen, Quang Uy, Nguyen, Diep N., Hoang, Dinh Thai, Dutkiewicz, Eryk

“…We develop a novel deep learning model, Multi-distributed Variational AutoEncoder (MVAE…”
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Variational Autoencoder-Based Hybrid Recommendation With Poisson Factorization for Modeling Implicit Feedback Autor Tanuma, Iwao, Matsui, Tomoko

“… We present a method that uses a hybrid recommendation framework based on collaborative filtering that models the number of interactions as a Poisson-distributed and variational autoencoder-based…”
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Detecting Malicious Gradients from Asynchronous SGD on Variational Autoencoder Autor Gu, Zhipin, Yang, Yuexiang, Shi, Heyuan

“… from the normal asynchronous training process. This paper proposes Asynvae, a robust distributed asynchronous learning framework where the parameter server uses variational autoencoder to detect…”
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DAS-Accelerometer Data Fusion With Semi-Supervised Graph Variational Autoencoder for In-Service Train Wheel Flat Detection Autor Dong, Yiqing, Han, Chengjia, Qu, Shuai, Zhao, Chaoyang, Madan, Aayush, Fu, Yuguang, Yang, Yaowen

“…) and accelerometers, with a novel Graph Vector-Quantization Variational AutoEncoder (GVQVAE) as the core component…”
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Variational Autoencoder-Based Hybrid Recommendation With Poisson Factorization for Modeling Implicit Feedback Autor Iwao Tanuma, Tomoko Matsui

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