Search Results - Variational autoencoder

3D‐Var data assimilation using a variational autoencoder by Melinc, Boštjan, Zaplotnik, Žiga

“… Here, an alternative neural network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three…”
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design by Mak, Hugo Wai Leung, Han, Runze, Yin, Hoover H. F.

“…In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction…”
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The shape variational autoencoder: A deep generative model of part‐segmented 3D objects by Nash, C., Williams, C. K. I.

“…We introduce a generative model of part‐segmented 3D objects: the shape variational auto‐encoder (ShapeVAE…”
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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…”
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Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders by Schonfeld, Edgar, Ebrahimi, Sayna, Sinha, Samarth, Darrell, Trevor, Akata, Zeynep

“… In this work, we take feature generation one step further and propose a model where a shared latent space of image features and class embeddings is learned by modality-specific aligned variational autoencoders…”
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Multi-Channel Multi-Scale Convolution Attention Variational Autoencoder (MCA-VAE): An Interpretable Anomaly Detection Algorithm Based on Variational Autoencoder by Liu, Jingwen, Huang, Yuchen, Wu, Dizhi, Yang, Yuchen, Chen, Yanru, Chen, Liangyin, Zhang, Yuanyuan

“…; some algorithms that consider both types of features lack interpretability. Therefore, we propose a high-precision, interpretable anomaly detection algorithm based on variational autoencoder (VAE…”
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MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling by Martí-Juan, Gerard, Lorenzi, Marco, Piella, Gemma

“…•A multi-channel model based on recurrent variational autoencoders was proposed to capture spatial and temporal evolution of AD using multimodal data…”
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CTVAE: Contrastive Tabular Variational Autoencoder for imbalance data: CTVAE: Contrastive Tabular Variational Autoencoder for imbalance data by Wang, Alex X., Le, Minh Quang, Duong, Huu-Thanh, Van, Bay Nguyen, Nguyen, Binh P.

“… while neglecting the relationships with the majority class. To overcome these limitations, we propose the Contrastive Tabular Variational Autoencoder (CTVAE…”
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VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder by Wang, Dongfang, Gu, Jin

“… Therefore, scRNA-seq data are much noisier than traditional bulk RNA-seq data. In this study, we proposed the deep variational autoencoder for scRNA-seq data (VASC…”
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Recognition of multivariate geochemical anomalies using a geologically-constrained variational autoencoder network with spectrum separable module – A case study in Shangluo District, China by Zhao, Bo, Zhang, Dehui, Tang, Panpan, Luo, Xiaoyan, Wan, Haoming, An, Lin

“…This study has developed a novel variational autoencoder architecture by incorporating the spectrum separable module, termed SSM-VAE, so as to recognize the multi-mineral-species geochemical patterns…”
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Randomly generating three-dimensional realistic schistous sand particles using deep learning: Variational autoencoder implementation by Shi, Jia-jie, Zhang, Wei, Wang, Wei, Sun, Yun-han, Xu, Chuan-yi, Zhu, Hong-hu, Sun, Zheng-xing

“…, grading, and mechanical properties. In this paper, the variational-autoencoder (VAE), a generative deep-learning model, was used to randomly generate realistic three-dimensional (3D…”
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Multi‐scale spatial‐spectral attention network for multispectral image compression based on variational autoencoder by Kong, Fanqiang, Cao, Tongbo, Li, Yunsong, Li, Dan, Hu, Kedi

“…•A hyperprior-based multiscale spatial-spectral attention network is proposed for multispectral image compression.•A neuroscience-based attention is combined…”
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Deep generative model of RNAs based on variational autoencoder with context-free grammar by Terai, Goro, Asai, Kiyoshi

“… Results We present a novel deep generative model that integrates context-free grammar (CFG) with a variational autoencoder…”
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Uncovering neural substrates across Alzheimer's disease stages using contrastive variational autoencoder by Tang, Yan, Yang, Chao, Wang, Yuqi, Zhang, Yunhao, Xin, Jiang, Zhang, Hao, Xie, Hua

“…, individuals with mild cognitive impairment, and Alzheimer's disease via a contrastive variational autoencoder model…”
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Multimodal medical image‐to‐image translation via variational autoencoder latent space mapping by Liang, Zhiwen, Cheng, Mengjie, Ma, Jinhui, Hu, Ying, Li, Song, Tian, Xin

“… Purpose To develop a unified image translation method using variational autoencoder (VAE) latent space mapping, which enables flexible conversion between different medical imaging modalities to meet clinical demands…”
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Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder by Lopez-Alvis, Jorge, Laloy, Eric, Nguyen, Frédéric, Hermans, Thomas

“…When solving inverse problems in geophysical imaging, deep generative models (DGMs) may be used to enforce the solution to display highly structured spatial…”
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EXTENDING THE LEE–CARTER MODEL WITH VARIATIONAL AUTOENCODER: A FUSION OF NEURAL NETWORK AND BAYESIAN APPROACH by Miyata, Akihiro, Matsuyama, Naoki

“… autoencoder that performs the variational Bayesian estimation of a state…”
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Deep Learning and Infrared Spectroscopy: Representation Learning with a β-Variational Autoencoder by Grossutti, Michael, D'Amico, Joseph, Quintal, Jonathan, MacFarlane, Hugh, Quirk, Amanda, Dutcher, John R

“…-a) pipe by training a β-variational autoencoder (β-VAE) on a database of PEX-a pipe spectra…”
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Variations in Variational Autoencoders - A Comparative Evaluation by Wei, Ruoqi, Garcia, Cesar, El-Sayed, Ahmed, Peterson, Viyaleta, Mahmood, Ausif

“…Variational Auto-Encoders (VAEs) are deep latent space generative models which have been immensely successful in many applications such as image generation…”
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Dirichlet Variational Autoencoder by Joo, Weonyoung, Lee, Wonsung, Park, Sungrae, Moon, Il-Chul

“…•This paper is a study on Dirichlet prior in variational autoencoder.•Our model outperforms baseline variational autoencoders in the perspective of loglikelihood…”
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