Results 81 to 90 of about 13,859 (190)

Variational Autoencoder to Obtain High Resolution Wind Fields from Reanalysis Data

open access: yesWind
Accurate wind flow prediction is essential for various applications, including the placement of wind turbines and a multitude of environmental assessments.
Bernhard Rösch   +5 more
doaj   +1 more source

A tutorial on multi-view autoencoders using the multi-view-AE library

open access: yes
There has been a growing interest in recent years in modelling multiple modalities (or views) of data to for example, understand the relationship between modalities or to generate missing data. Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to ...
Aguila, Ana Lawry, Altmann, Andre
openaire   +2 more sources

A Multi-Level-Denoising Autoencoder Approach for Wind Turbine Fault Detection

open access: yesIEEE Access, 2019
The effective fault detection of wind turbines (WTs) can greatly help to improve their availability and reduce their operation and maintenance costs. In this context, data-driven fault detection approaches have attracted a lot of interests due to the ...
Xin Wu   +4 more
doaj   +1 more source

Ae$$^2$$I: A Double Autoencoder for Imputation of Missing Values

open access: yes
The most common strategy of imputing missing values in a table is to study either the column-column relationship or the row-row relationship of the data table, then use the relationship to impute the missing values based on the non-missing values from other columns of the same row, or from the other rows of the same column.
openaire   +2 more sources

AE-ViT: Token Enhancement for Vision Transformers via CNN-Based Autoencoder Ensembles

open access: yesInternational Journal of Artificial Intelligence & Applications
While Vision Transformers (ViTs) have revolutionized computer vision with their exceptional results, they struggle to balance processing speed with visual detail preservation. This tension becomes particularly evident when implementing larger patch sizes.
Heriniaina Andry RABOANARY   +2 more
openaire   +1 more source

Model Validation for Multivariate Functional Responses via Autoencoder-Based Dual-Layer Feature Extraction

open access: yesMathematics
Model validation for complex simulation models with multivariate functional responses poses significant challenges, as it involves the dual coupling of physical correlations among variables and field correlations in time-series data.
Dengyu Wu   +5 more
doaj   +1 more source

Multi-view-AE: A Python package for multi-view autoencoder models

open access: yesJournal of Open Source Software, 2023
Ana Lawry Aguila   +4 more
openaire   +2 more sources

NN-AE-VQE: Neural network parameter prediction on autoencoded variational quantum eigensolvers

open access: yes
A longstanding computational challenge is the accurate simulation of many-body particle systems. Especially for deriving key characteristics of high-impact but complex systems such as battery materials and high entropy alloys (HEA). While simple models allow for simulations of the required scale, these methods often fail to capture the complex dynamics
Mesman, Koen   +4 more
openaire   +2 more sources

Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis

open access: yesScientific Reports
Periodontitis, a chronic inflammatory condition of the periodontium, is associated with over 60 systemic diseases. Despite advancements, precision medicine approaches have had limited success, emphasizing the need for deeper insights into cellular ...
Pradeep Kumar Yadalam   +2 more
doaj   +1 more source

Data Augmentation for Text Classification Using Autoencoders

open access: yesIEEE Access
Deep learning models have greatly improved various natural language processing tasks. However, their effectiveness depends on large data sets, which can be difficult to acquire.
Mustafa Cataltas   +2 more
doaj   +1 more source

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