Search Results - Unsupervised autoencoder model

Learning particle dynamics: from diffusion to interactions

Authors: Fernández Fernández, Gabriel

Contributors: University/Department: Universitat Politècnica de Catalunya. Institut de Ciències Fotòniques

Thesis Advisors: Lewenstein, Maciej, Manzo, Carlo

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Unsupervised, Machine Learning, Variational Autoencoder, Feature Learning, Representation Learning, Autoregressive Model, Data Analysis, Knowledge Discovery, Interpretability, Biophysics, Anomalous Diffusion, Single Trajectory Characterization, Time Series, Stochastic Model, Brownian Motion, Fractional Brownian Motion, Scaled Brownian Motion, Confined Brownian Motion, Graph Neural Network, Lennard-Jones, Non-reciprocal Force, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació, Àrees temàtiques de la UPC::Informàtica, 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions, 004 - Informàtica, 577 - Bioquímica. Biologia molecular. Biofísica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/696076
https://dx.doi.org/10.5821/dissertation-2117-448803

Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model

Authors: Lingtao Su Chunhui Xu Shuai Zeng et al.

Source: Front Plant Sci
Frontiers in Plant Science, Vol 13 (2022)

Subject Terms: autoencoder, 0301 basic medicine, 2. Zero hunger, 0303 health sciences, 03 medical and health sciences, transcriptome analysis, tissue-specific gene, deep learning, Plant culture, gene regulatory network, Plant Science, soybean, SB1-1110

Access URL: https://www.frontiersin.org/articles/10.3389/fpls.2022.831204/pdf
https://pubmed.ncbi.nlm.nih.gov/35310659
https://doaj.org/article/acf6d717dcc14e73a5378536d91ccc29

Leveraging productivity indicators for anomaly detection in swine breeding herds with unsupervised learning.

Authors: Pedro Mil-Homens, Mafalda Wang, Chong Trevisan, Giovani et al.

Source: Frontiers in Veterinary Science. 2025, p1-16. 16p.

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification.

Authors: Johnsen, Timothy K. Bi, Xiangyu Chou, Chunwei et al.

Source: Water Resources Research; Oct2025, Vol. 61 Issue 10, p1-23, 23p

Subject Terms: EVAPOTRANSPIRATION, AUTOENCODERS, STOCHASTIC analysis, MACHINE learning, HYDROLOGICAL forecasting, NOISE control, TELEMETRY

Convolution Autoencoder based Classification Model for Content Based Image Retrieval.

Authors: Rai, Rishi Sisodia, Dilip Singh

Source: Procedia Computer Science. 2025, Vol. 258, p1865-1876. 12p.

Subject Terms: Content-based image retrieval, Convolutional neural networks, Image recognition (Computer vision), Autoencoders, Binary codes, Deep learning

Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification.

Authors: Mansour RF Escorcia-Gutierrez J Gamarra M et al.

Source: Pattern recognition letters [Pattern Recognit Lett] 2021 Nov; Vol. 151, pp. 267-274. Date of Electronic Publication: 2021 Sep 22.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 9879988 Publication Model: Print-Electronic Cited Medium: Print ISSN: 0167-8655 (Print) Linking ISSN: 01678655 NLM ISO Abbreviation: Pattern Recognit Lett Subsets: PubMed not MEDLINE

Unsupervised anomaly detection in industrial machines supported by vibration analysis under data scarcity constraints

Authors: Torres, Pedro Spencer, Geoffrey Esteves, Arthur et al.

Contributors: Torres, Pedro Spencer, Geoffrey Esteves, Arthur et al.

Subject Terms: Condition monitoring, Anomaly detection, Vibration analysis, Unsupervised learning, Data scarcity, LSTM Autoencoder

File Description: application/pdf

Availability: http://hdl.handle.net/10400.11/10338

Enhancing Fraud Detection in the Insurance Industry: Integrating SHAP explanations into an Unsupervised Anomaly Detection Model with Autoencoder-based Dimensionality Reduction

Authors: Costa, João Filipe Dias Gomes de Morais Henriques, Roberto André Pereira RUN

Contributors: Costa, João Filipe Dias Gomes de Morais Henriques, Roberto André Pereira RUN

Subject Terms: Health Insurance, Fraud Detection, Unsupervised Learning, Anomaly Detection, Autoencoder, SHAP, SDG 8 - Decent work and economic growth, SDG 9 - Industry, innovation and infrastructure, SDG 16 - Peace, justice and strong institutions, Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação

File Description: application/pdf

Availability: http://hdl.handle.net/10362/164589

Unsupervised learning with a physics-based autoencoder for estimating the thickness and mixing ratio of pigments

Authors: Shitomi, Ryuta Tsuji, Mayuka 39 et al.

Index Terms: NA

URL: http://hdl.handle.net/10061/0002000515
https://naist.repo.nii.ac.jp/records/2000515
https://doi.org/10.1364/JOSAA.472775
https://opg.optica.org/josaa/fulltext.cfm?uri=josaa-40-1-116&id=524419
https://doi.org/10.1364/JOSAA.472775
https://opg.optica.org/josaa/fulltext.cfm?uri=josaa-40-1-116&id=524419

Detecting Fraudulent Wallets in Ethereum Blockchain Combining Supervised and Unsupervised Techniques

Using Autoencoders and XGboost

Authors: Crisostomo, Joao Lobo, Victor Bacao, Fernando et al.

Contributors: Crisostomo, Joao Lobo, Victor Bacao, Fernando et al.

Subject Terms: Anomaly detection, Ethereum, Blockchain, Autoencoder, XGBoost, Fraud Detection, Malicious Accounts, Machine Learning, SDG 9 - Industry, Innovation, and Infrastructure, SDG 16 - Peace, Justice and Strong Institutions

File Description: application/pdf

Relation: 978-3-031-45154-6; 2367-3370; PURE: 76402195

Availability: http://hdl.handle.net/10362/160270

New immune-inspired AI algorithm for anomaly detection

Authors: Sousa, Bruno Lopes de

Subject Terms: Anomaly detection, Unsupervised learning, Artificial immune systems, Model interpretability, Early detection, Biomedical data, Classification

File Description: application/pdf

Availability: http://hdl.handle.net/10773/45472

Unsupervised feature extraction with autoencoder : for the representation of parkinson´s disease patients

Authors: Kazak, Veronica Henriques, Roberto André Pereira Castelli, Mauro et al.

Contributors: Kazak, Veronica Henriques, Roberto André Pereira Castelli, Mauro et al.

Subject Terms: Autoencoder, Representation Learning, Feature Extraction, Unsupervised Learning, Deep Learning

File Description: application/pdf

Availability: http://hdl.handle.net/10362/71589

SPECULAR CORRECTION OF IMAGES USING AUTOENCODER NEURAL NETWORK MODEL

Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model.

Authors: Su, Lingtao Xu, Chunhui Zeng, Shuai et al.

Source: Frontiers in Plant Science; 3/3/2022, Vol. 13, p1-15, 15p

Subject Terms: GENE regulatory networks, GENE expression, TRANSCRIPTOMES, PLANT cells & tissues, GENE mapping, ROOT-tubercles

A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems.

Authors: Talaei Khoei, Tala Kaabouch, Naima

Source: Information. Feb2023, Vol. 14 Issue 2, p103. 14p.

Subject Terms: *Decision trees, Supervised learning, Principal components analysis, Regression trees, Comparative studies, Logistic regression analysis, False alarms

Unsupervised learning with a physics-based autoencoder for estimating the thickness and mixing ratio of pigments.

Authors: Tsuji, Mayuka 40908729 Fujimura, Yuki et al.

Index Terms: Journal Article., NA.

URL: http://hdl.handle.net/10061/0002000515
https://naist.repo.nii.ac.jp/records/2000515
https://doi.org/10.1364/JOSAA.472775
https://opg.optica.org/josaa/fulltext.cfm?uri=josaa-40-1-116&id=524419

Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images.

Authors: Georgescu, Mariana-Iuliana¹ (AUTHOR) lily@yahoo.com

Source: Procedia Computer Science. 2023, Vol. 225, p969-978. 10p.

Subject Terms: Computer-assisted image analysis (Medicine), Diagnostic imaging, Medical masks, Intrusion detection systems (Computer security), Image reconstruction, Deep learning

Data-driven methods to characterize heterogeneity in Alzheimer’s disease using cross-sectional and longitudinal data

Authors: Martí Juan, Gerard

Contributors: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: Piella Fenoy, Gemma, Sanromà, Gerard

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Alzheimer’s disease, Dementia, Machine learning, Disease progression, Computer-aided diagnosis, Disease subtpying, Longitudinal data, Variational autoencoder, APOE, Hippocampus, MRI, Alzheimer, Demència, Progressió de l’enfermetat, Diagnosis assistit per ordinador, Subtipatge, Dades longitudinals, Hipocamp

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/671269

Study and design of classification algorithms for diagnosis and prognosis of failures in wind turbines from SCADA data

Authors: Blanco Martínez, Alejandro

Contributors: University/Department: Universitat de Vic - Universitat Central de Catalunya. Departament d'Enginyeries

Thesis Advisors: Solé-Casals, Jordi, Martí i Puig, Pere, Cusidó Roura, Jordi

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: SOM, Deep Learning, LSTM, Autoencoder, Turbina eòlica, Selecció de variables, Valors extrems, Clusterització, Enginyeria

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/586097

ロバスト性，正則化，タスク不変性に関する変分オートエンコーダの改善

Authors: 高橋, 大志 鹿島, 久嗣 山本, 章博 et al.

Contributors: 高橋, 大志 鹿島, 久嗣 山本, 章博 et al.

Subject Terms: Variatinoal Autoencoder, Deep Generative Model, Unsupervised Learning, Representation Learning, Deep Learning

File Description: application/pdf

Access URL: https://ndlsearch.ndl.go.jp/books/R100000039-I12911287

Degree: 博士(情報学) -- 京都大学, Kyoto University