Suchergebnisse - Deep regularized variational autoencoder

Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process von Yan, Xiaoan, She, Daoming, Xu, Yadong, Jia, Minping

“… Hence, this paper proposes a novel deep learning model named deep regularized variational autoencoder (DRVAE …”
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Hyperspectral Anomaly Detection Based On Graph Regularized Variational Autoencoder von Wei, Jie, Zhang, Jingfa, Xu, Yang, Xu, Lidan, Wu, Zebin, Wei, Zhihui

“… (HAD). In order to further utilize the spatial information in hyperspectral images (HSIs), an anomaly detection method for HSIs is presented based on graph regularized variational autoencoder (GRVAE …”
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FVAE: a regularized variational autoencoder using the Fisher criterion von Lai, Jie, Wang, Xiaodan, Xiang, Qian, Li, Rui, Song, Yafei

“… As a deep generative model, the variational autoencoder (VAE) is widely applied to solve problems of insufficient samples and imbalanced labels …”
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MSARAE: Multiscale adversarial regularized autoencoders for cortical network classification von Zhu, Yihui, Zhou, Yue, Zhang, Xiaotong, Li, Yueying, Yuan, Yonggui, Kong, Youyong

“… •An adversarial regularization module is introduced to improve the accuracy of multi-scale graph variational autoencoder generation …”
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PRVNet: A Novel Partially-Regularized Variational Autoencoders for Massive MIMO CSI Feedback von Hussien, Mostafa, Nguyen, Kim Khoa, Cheriet, Mohamed

“… In this paper, we introduce PRVNet, a neural network architecture inspired by variational autoencoders (VAE …”
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Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation von Huang, Qi, Qiao, Chen, Jing, Kaili, Zhu, Xu, Ren, Kai

“… Graph regularized sparse deep autoencoder (GSDAE) can reconstruct sparse samples and keep the manifold structure of data which will facilitate biomarkers selection greatly …”
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Molecular Generative Model Based on an Adversarially Regularized Autoencoder von Hong, Seung Hwan, Ryu, Seongok, Lim, Jaechang, Kim, Woo Youn

“… A variety of models reported so far are based on either a variational autoencoder (VAE) or a generative adversarial network (GAN …”
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A deep imputation and inference framework for estimating personalized and race-specific causal effects of genomic alterations on PSA von Chen, Zhong, Cao, Bo, Edwards, Andrea, Deng, Hongwen, Zhang, Kun

“… In light of these issues, we propose a data-driven, deep learning-based imputation and inference framework (DIIF …”
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Attri-VAE: Attribute-based interpretable representations of medical images with variational autoencoders von Cetin, Irem, Stephens, Maialen, Camara, Oscar, González Ballester, Miguel A.

“… facilitating their use in the reasoning behind the medical decisions. Latent space representations built with variational autoencoders (VAE …”
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Similarity-assisted variational autoencoder for nonlinear dimension reduction with application to single-cell RNA sequencing data von Kim, Gwangwoo, Chun, Hyonho

“… patterns or identifying outliers. The variational autoencoder (VAE) is a popular deep generative method equipped with encoder/decoder structures …”
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Predicting chemotherapy response using a variational autoencoder approach von Wei, Qi, Ramsey, Stephen A.

“… Recently, multiple studies have established the utility of a deep neural network approach, the variational autoencoder (VAE …”
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ERLD-HC: Entropy-Regularized Latent Diffusion for Harmony-Constrained Symbolic Music Generation von Li, Yang

“… ), which combines a variational autoencoder (VAE) and latent diffusion models with an entropy-regularized conditional random field (CRF …”
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Deep Multi-Task Learning for an Autoencoder-Regularized Semantic Segmentation of Fundus Retina Images von Jin, Ge, Chen, Xu, Ying, Long

“… Automated segmentation of retinal blood vessels is necessary for the diagnosis, monitoring, and treatment planning of the disease. Although current U-shaped …”
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Spatially Constrained Variational Autoencoder for Geochemical Data Denoising and Uncertainty Quantification von Huang, Dazheng, Zuo, Renguang, Wang, Jian, Tolosana-Delgado, Raimon

“… This study proposes a novel deep learning framework, the Spatially Constrained Variational Autoencoder (SC-VAE …”
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A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices von Tucci, Mauro, Barmada, Sami, Formisano, Alessandro, Thomopulos, Dimitri

“… The use of behavioral models based on deep learning (DL) to accelerate electromagnetic field computations has recently been proposed to solve complex electromagnetic problems …”
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Graph Regularized Variational Ladder Networks for Semi-Supervised Learning von Hu, Cong, Song, Xiao-Ning

“… To tackle the problem of semi-supervised learning (SSL), we propose a new autoencoder-based deep model. Ladder networks (LN …”
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Data Augmentation with Cross-Modal Variational Autoencoders (DACMVA) for Cancer Survival Prediction von Rajaram, Sara, Mitchell, Cassie S.

“… The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs …”
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Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders von Gros, Benedikt, Wunder, Gerhard

“… If a record is not real, then how could it violate a person's privacy? In addition, deep-learning based generative models are employed successfully to approximate complex …”
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Copula in Variational Autoencoders von Quint, Anthony

“… Variational inference algorithms seek to estimate the posterior of latent variables using anapproximate inference model …”
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Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders von Groß, Benedikt, Wunder, Gerhard

“… If a record is not real, then how could it violate a person's privacy? In addition, deep-learning based generative models are employed successfully to approximate complex …”
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