Search Results - (( Autoencoder applications ) OR ( Autoencoder publications ))

An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing by Shankar, Venkatesh, Parsana, Sohil

“…) models, have surged in popularity for analyzing unstructured data in marketing. Yet, we do not fully understand which NLP models are appropriate for which marketing applications and what insights can be best derived…”
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Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks by Aqel, Nedal, Reusser, Lea, Margreth, Stephan, Carminati, Andrea, Lehmann, Peter

“…Information on soil water potential is essential to assessing the soil moisture state, to prevent soil compaction in weak soils, and to optimize crop…”
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Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath by Soleymani, Farzan, Paquet, Eric

“…•Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy…”
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Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study by Cha, Dongchul, Sung, MinDong, Park, Yu-Rang

“…Background: Machine learning (ML) is now widely deployed in our everyday lives. Building robust ML models requires a massive amount of data for training…”
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Polytopic autoencoders with smooth clustering for reduced-order modeling of flows by Heiland, Jan, Kim, Yongho

“…With the advancement of neural networks, there has been a notable increase, both in terms of quantity and variety, in research publications concerning the application of autoencoders to reduced-order models…”
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RETRACTED: Pre-training graph autoencoder incorporating hierarchical topology knowledge by Zhu, Hongyin, Li, Yakun, Liu, Luyang, Tong, Haonan, Lin, Qunyang, Zhang, Chuang

“… Concerns were raised following the publication of the paper titled “Pre-training Graph Autoencoder Incorporating Hierarchical Topology Knowledge” (DOI: https://doi.org/10.1016/j.eswa.2024.125976…”
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Slow feature‐constrained decomposition autoencoder: Application to process anomaly detection and localization by Jia, Mingwei, Jiang, Lingwei, Hu, Junhao, Liu, Yi, Chen, Tao

“… To address this challenge, we propose a slow feature‐constrained decomposition autoencoder (SFC‐DAE…”
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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping by Sattarov, Boris, Baskin, Igor I, Horvath, Dragos, Marcou, Gilles, Bjerrum, Esben Jannik, Varnek, Alexandre

“…Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest…”
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Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology by Janowczyk, Andrew, Basavanhally, Ajay, Madabhushi, Anant

“…•Stain Normalization using Sparse AutoEncoders (StaNoSA) in introduced.•It standardizes color distributions of a test image to a single template image…”
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Optimizing Large Scale Problems With Metaheuristics in a Reduced Space Mapped by Autoencoders-Application to the Wind-Hydro Coordination by Miranda, Vladimiro, da Hora Martins, Joana, Palma, Vera

“… The technique applies autoencoders as a reversible mapping between the original problem space and a reduced space…”
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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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A new investment method with AutoEncoder: Applications to crypto currencies by Nakano, Masafumi, Takahashi, Akihiko

“…•AutoEncoder extracts the factors which enable to prevent the large drawdown.•The extracted non-linear factors are implemented by the dynamic delta hedging…”
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Disentangled-Multimodal Adversarial Autoencoder: Application to Infant Age Prediction With Incomplete Multimodal Neuroimages by Hu, Dan, Zhang, Han, Wu, Zhengwang, Wang, Fan, Wang, Li, Smith, J. Keith, Lin, Weili, Li, Gang, Shen, Dinggang

“…Effective fusion of structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) data has the potential to boost the accuracy…”
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Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data by Simeon, Andri, Pérez-Guillén, Cristina, Volpi, Michele, Seupel, Christine, van Herwijnen, Alec

“…Monitoring snow avalanche activity is essential for operational avalanche forecasting and the successful implementation of mitigation measures to ensure safety…”
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A comprehensive survey on design and application of autoencoder in deep learning by Li, Pengzhi, Pei, Yan, Li, Jianqiang

“… Researchers have proposed several improved versions of autoencoder based on different application fields…”
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A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network by Wang, Lei, You, Zhu-Hong, Chen, Xing, Xia, Shi-Xiong, Liu, Feng, Yan, Xin, Zhou, Yong, Song, Ke-Jian

“… In this article, we propose a new computational method for predicting DTIs from drug molecular structure and protein sequence by using the stacked autoencoder of deep learning, which can adequately…”
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Development of a novel parallel framework upon deep dual‐enhanced autoencoder and its applications for industrial soft sensing by Chen, Xu, Shao, Weiming, Wei, Chihang

“…In recent years, data‐driven soft sensing technology has provided a cost‐effective support for industrial process monitoring, in which autoencoder plays an important role in extracting features for soft sensing technology…”
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SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising by Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam

“… This study represents a deep learning based approach to denoising images and restoring features using stack denoising convolutional autoencoder…”
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Recent Research and Applications in Variational Autoencoders for Industrial Prognosis and Health Management: A Survey by Zemouri, Ryad, Levesque, Melanie, Boucher, Etienne, Kirouac, Mathieu, Lafleur, Francois, Bernier, Simon, Merkhouf, Arezki

“… The common particularity of all these application domains is that a great part of this data is mostly unlabeled…”
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1D-CONVOLUTIONAL AUTOENCODER BASED HYPERSPECTRAL DATA COMPRESSION by Kuester, J., Gross, W., Middelmann, W.

“…Hyperspectral sensor technology has been advancing in recent years and become more practical to tackle a variety of applications…”
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