Search Results - Deep regularized variational autoencoder

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

“… Hence, this paper proposes a novel deep learning model named deep regularized variational autoencoder (DRVAE…”
Get full text

Hyperspectral Anomaly Detection Based On Graph Regularized Variational Autoencoder by 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…”
Get full text

FVAE: a regularized variational autoencoder using the Fisher criterion by 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…”
Get full text

MSARAE: Multiscale adversarial regularized autoencoders for cortical network classification by 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…”
Get full text

PRVNet: A Novel Partially-Regularized Variational Autoencoders for Massive MIMO CSI Feedback by Hussien, Mostafa, Nguyen, Kim Khoa, Cheriet, Mohamed

“… In this paper, we introduce PRVNet, a neural network architecture inspired by variational autoencoders (VAE…”
Get full text

Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation by 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…”
Get full text

Molecular Generative Model Based on an Adversarially Regularized Autoencoder by 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…”
Get more information

A deep imputation and inference framework for estimating personalized and race-specific causal effects of genomic alterations on PSA by 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…”
Get more information

Attri-VAE: Attribute-based interpretable representations of medical images with variational autoencoders by 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…”
Get full text

Similarity-assisted variational autoencoder for nonlinear dimension reduction with application to single-cell RNA sequencing data by Kim, Gwangwoo, Chun, Hyonho

“… patterns or identifying outliers. The variational autoencoder (VAE) is a popular deep generative method equipped with encoder/decoder structures…”
Get full text

Predicting chemotherapy response using a variational autoencoder approach by Wei, Qi, Ramsey, Stephen A.

“… Recently, multiple studies have established the utility of a deep neural network approach, the variational autoencoder (VAE…”
Get full text

ERLD-HC: Entropy-Regularized Latent Diffusion for Harmony-Constrained Symbolic Music Generation by Li, Yang

“…), which combines a variational autoencoder (VAE) and latent diffusion models with an entropy-regularized conditional random field (CRF…”
Get full text

Deep Multi-Task Learning for an Autoencoder-Regularized Semantic Segmentation of Fundus Retina Images by 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…”
Get full text

Spatially Constrained Variational Autoencoder for Geochemical Data Denoising and Uncertainty Quantification by Huang, Dazheng, Zuo, Renguang, Wang, Jian, Tolosana-Delgado, Raimon

“… This study proposes a novel deep learning framework, the Spatially Constrained Variational Autoencoder (SC-VAE…”
Get full text

A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices by 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…”
Get full text

Graph Regularized Variational Ladder Networks for Semi-Supervised Learning by 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…”
Get full text

Data Augmentation with Cross-Modal Variational Autoencoders (DACMVA) for Cancer Survival Prediction by Rajaram, Sara, Mitchell, Cassie S.

“…The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs…”
Get full text

Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders by 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…”
Get full text

Copula in Variational Autoencoders by Quint, Anthony

“…Variational inference algorithms seek to estimate the posterior of latent variables using anapproximate inference model…”
Get full text

Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders by 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…”
Get full text