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   Articles with "variational autoencoder" as a keyword



An attempt to construct the individual model of daily facial skin temperature using variational autoencoder

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recommendations! Published in 2021 at "Artificial Life and Robotics"

DOI: 10.1007/s10015-021-00699-7

Abstract: Facial skin temperature (FST) has also gained prominence as an indicator for detecting anomalies such as fever due to the COVID-19. When FST is used for engineering applications, it is enough to be able to… read more here.

Keywords: skin temperature; facial skin; variational autoencoder; using variational ... See more keywords

SeqVAE: Sequence variational autoencoder with policy gradient

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recommendations! Published in 2021 at "Applied Intelligence"

DOI: 10.1007/s10489-021-02374-7

Abstract: In the paper, we propose a variant of Variational Autoencoder (VAE) for sequence generation task, called SeqVAE, which is a combination of recurrent VAE and policy gradient in reinforcement learning. The goal of SeqVAE is… read more here.

Keywords: policy gradient; policy; seqvae; variational autoencoder ... See more keywords
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Augmenting deviation of faults from the normal using fault assistant Gaussian mixture prior variational autoencoder

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recommendations! Published in 2021 at "Journal of the Taiwan Institute of Chemical Engineers"

DOI: 10.1016/j.jtice.2021.06.015

Abstract: Abstract In this new era of Industry 4.0, manufacturers tend to store process data from the entire production, regardless of whether they are “normal” or “faulty” for further data analysis. However, almost all the existing… read more here.

Keywords: prior variational; variational autoencoder; mixture prior; fault ... See more keywords

Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder

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recommendations! Published in 2022 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.1c01573

Abstract: Some of the most common applications of machine learning (ML) algorithms dealing with small molecules usually fall within two distinct domains, namely, the prediction of molecular properties and the design of novel molecules with some… read more here.

Keywords: prediction molecular; molecular properties; variational autoencoder; grammar variational ... See more keywords

Dynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO.

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recommendations! Published in 2021 at "Journal of chemical theory and computation"

DOI: 10.1021/acs.jctc.1c00870

Abstract: An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen-major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined… read more here.

Keywords: variational autoencoder; optimization; convolutional variational; mhc binding ... See more keywords

Deep learning on the 2-dimensional Ising model to extract the crossover region with a variational autoencoder

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recommendations! Published in 2020 at "Scientific Reports"

DOI: 10.1038/s41598-020-69848-5

Abstract: The 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The encoded… read more here.

Keywords: variational autoencoder; crossover region; dimensional ising; ising model ... See more keywords

Research on multi-heat source arrangement optimization based on equivalent heat source method and reconstructed variational autoencoder

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-71284-8

Abstract: The variational autoencoder (VAE) architecture has significant advantages in predictive image generation. This study proposes a novel RFCNN-βVAE model, which combines residual-connected fully connected neural networks with VAE to handle multi-heat source arrangements. By integrating… read more here.

Keywords: heat; heat source; variational autoencoder; multi heat ... See more keywords

A hidden feature label propagation method based on deep convolution variational autoencoder for fault diagnosis

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recommendations! Published in 2022 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ac4ffa

Abstract: Vibration signal of mechanical component usually exhibits non-linear and non-stationary characteristics, the key step of fault diagnosis is to extract discriminant features hidden in the vibration signal, in order to improve diagnostic performance and identify… read more here.

Keywords: label propagation; method; variational autoencoder; fault diagnosis ... See more keywords

An LSTM-based adversarial variational autoencoder framework for self-supervised neural decoding of behavioral choices

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recommendations! Published in 2024 at "Journal of Neural Engineering"

DOI: 10.1088/1741-2552/ad3eb3

Abstract: Objective.This paper presents data-driven solutions to address two challenges in the problem of linking neural data and behavior: (1) unsupervised analysis of behavioral data and automatic label generation from behavioral observations, and (2) extraction of… read more here.

Keywords: autoencoder; variational autoencoder; neural decoding; adversarial variational ... See more keywords

Dimensionality reduction and visualization of single-cell RNA-seq data with an improved deep variational autoencoder.

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recommendations! Published in 2023 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbad152

Abstract: Single-cell RNA sequencing (scRNA-seq) is a revolutionary breakthrough that determines the precise gene expressions on individual cells and deciphers cell heterogeneity and subpopulations. However, scRNA-seq data are much noisier than traditional high-throughput RNA-seq data because… read more here.

Keywords: seq data; cell; scrna seq; seq ... See more keywords

FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis

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recommendations! Published in 2025 at "Briefings in Bioinformatics"

DOI: 10.1093/bib/bbaf157

Abstract: Abstract Single-cell multi-omics technologies have revolutionized the study of cell states and functions by simultaneously profiling multiple molecular layers within individual cells. However, existing methods for integrating these data struggle to preserve critical feature information… read more here.

Keywords: variational autoencoder; multi omics; single cell; cell ... See more keywords