Výsledky vyhledávání - "bayesian autoencoder"

Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain MRI Analysis

Autoři: Dip Roy

Identifying Anomalous Behavior in Aircraft Landing Trajectory Using a Bayesian Autoencoder

Autoři: Yingxiao Kong Sankaran Mahadevan

Zdroj: Journal of Aerospace Information Systems. 21:19-27

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences

Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain 2 MRI Analysis

Autoři: Roy, Dip

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2504.15562

Variational Bayesian Autoencoder for Channel Compression and Feedback in Massive MIMO Systems

Autoři: Xuanyu Zheng Yuanyuan Bi Huayan Guo a další

Zdroj: ICC 2023 - IEEE International Conference on Communications. :6349-6354

Variational Bayesian Autoencoder for Channel Compression and Feedback in Massive MIMO Systems

Autoři: Zheng, Xuanyu Bi, Yuanyuan Guo, Huayan a další

Témata: CSI compression, Conference paper

URL: http://repository.hkust.edu.hk/ir/Record/1783.1-126887
https://doi.org/10.1109/ICC45041.2023.10278811
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=1550-3607&rft.volume=2023-May&rft.issue=&rft.date=2023&rft.spage=6349&rft.aulast=Zheng&rft.aufirst=Xuanyu&rft.atitle=Variational+Bayesian+Autoencoder+for+Channel+Compression+and+Feedback+in+Massive+MIMO+Systems&rft.title=IEEE+International+Conference+on+Communications
http://www.scopus.com/record/display.url?eid=2-s2.0-85178308003&origin=inward
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=001094862606078

Least Square Variational Bayesian Autoencoder with Regularization

Autoři: Ramachandra, Gautam

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Machine Learning (stat.ML), 02 engineering and technology, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/1707.03134

Bayesian AutoEncoder: Generation of Bayesian Networks with Hidden Nodes for Features

Autoři: Kaneharu Nishino Mary Inaba

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence. 30

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Explaining Probabilistic Bayesian Neural Networks for Cybersecurity Intrusion Detection

Autoři: Tengfei Yang Yuansong Qiao Brian Lee

Zdroj: IEEE Access, Vol 12, Pp 97004-97016 (2024)
IEEE Access

Témata: Bayesian explanation, uncertainty quantification, explainability, aleatoric and epistemic uncertainties, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences, Bayesian autoencoder, TK1-9971

Přístupová URL adresa: https://doaj.org/article/68d19046fec441b2af9adfeb613824ca

Code implementation of the Bayesian autoencoder from Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants

Autoři: L. Mars Gao J. Nathan Kutz

Témata: Applications in physical sciences, Artificial intelligence not elsewhere classified, Numerical solution of differential and integral equations, Ordinary differential equations, difference equations and dynamical systems, Partial differential equations, model discovery, dynamical systems, machine learning, Bayesian deep learning, Bayesian sparse inference, autoencoder

Dostupnost: https://doi.org/10.6084/m9.figshare.25283455.v1
https://figshare.com/articles/dataset/Code_implementation_of_the_Bayesian_autoencoder_from_Bayesian_autoencoders_for_data-driven_discovery_of_coordinates_governing_equations_and_fundamental_constants/25283455

The filling-in function of the Bayesian AutoEncoder Network

Autoři: Kaneharu Nishino Mary Inaba

Zdroj: SPIE Proceedings. 10443:104431E

Témata: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences

Přístupová URL adresa: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10443/1/The-filling-in-function-of-the-Bayesian-AutoEncoder-Network/10.1117/12.2280931.full
http://ui.adsabs.harvard.edu/abs/2017SPIE10443E..1EN/abstract

Bayesian autoencoders for anomaly detection : design, uncertainty quantification, and explainability with industrial applications

Autoři: Yong, Bang Xiang Brintrup, Alexandra

Přispěvatelé: Yong, Bang Xiang Brintrup, Alexandra

Témata: anomaly detection, bayesian autoencoder, explainable ai, uncertainty quantification, unsupervised neural networks

Přístupová URL adresa: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.871684

Bayesian Autoencoders for Drift Detection in Industrial Environments

Autoři: Yong, BX Fathy, Y Brintrup, A a další

Přispěvatelé: Yong, BX Fathy, Y Brintrup, A a další

Zdroj: 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT. :627-631

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, deep learning, 02 engineering and technology, uncertainty, sensors, Bayesian autoencoder, Machine Learning (cs.LG)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/pdf/2107.13249
http://arxiv.org/abs/2107.13249
http://dblp.uni-trier.de/db/conf/metroi/metroi2020.html#YongFB20
https://ieeexplore.ieee.org/document/9138306/
https://arxiv.org/abs/2107.13249
https://dblp.uni-trier.de/db/journals/corr/corr2107.html#abs-2107-13249
https://arxiv.org/abs/2107.13249v1
http://export.arxiv.org/pdf/2107.13249
https://arxiv.org/pdf/2107.13249
http://ui.adsabs.harvard.edu/abs/2021arXiv210713249Y/abstract

Bayesian Autoencoder for Trigger-less Anomaly Detection

Autoři: DI PRIMA, GIACOMO ZANETTI, MARCO

Přispěvatelé: DI PRIMA, GIACOMO ZANETTI, MARCO

Témata: DeepLearning, ComputationalPhysics, AnomayDetection

Popis souboru: application/pdf

Relation: Dipartimento di Fisica e Astronomia "Galileo Galilei" - DFA; PHYSICS OF DATA Laurea Magistrale (D.M. 270/2004); 2023; https://hdl.handle.net/20.500.12608/70126

Dostupnost: https://hdl.handle.net/20.500.12608/70126

Towards trustworthy cybersecurity operations using Bayesian Deep Learning to improve uncertainty quantification of anomaly detection.

Autoři: Yang, Tengfei Qiao, Yuansong Lee, Brian

Zdroj: Computers & Security. Sep2024, Vol. 144, pN.PAG-N.PAG. 1p.

Témata: ANOMALY detection (Computer security), DEEP learning, FALSE alarms, TRUST, INTERNET security, INTRUSION detection systems (Computer security)

Bayesian Autoencoder for Trigger-less Anomaly Detection

Autoři: DI PRIMA, GIACOMO#idabnull

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/20.500.12608/70126

Drift detection methods for data streams ; Poikkeamien tunnistaminen aikasarjadatasta

Autoři: Hakkarainen, Riina Keisala, Jukka Perustieteiden korkeakoulu a další

Přispěvatelé: Hakkarainen, Riina Keisala, Jukka Perustieteiden korkeakoulu a další

Témata: drift detection, anomaly detection, regression, Bayesian autoencoder, statistical tests

Popis souboru: 48 + 6; application/pdf

Relation: https://aaltodoc.aalto.fi/handle/123456789/120924

Dostupnost: https://aaltodoc.aalto.fi/handle/123456789/120924

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes

Autoři: Tran, Ba-Hien Shahbaba, Babak Mandt, Stephan a další

Témata: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2302.04534

Bayesian Autoencoders for Drift Detection in Industrial Environments

Autoři: Yong, BX Fathy, Y Brintrup, A

Témata: uncertainty, Bayesian autoencoder, deep learning, sensors, Conference Object

URL: https://www.repository.cam.ac.uk/handle/1810/326149

Revisiting Bayesian Autoencoders with MCMC

Autoři: Chandra, Rohitash Jain, Mahir Maharana, Manavendra a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Applications, text

URL: http://arxiv.org/abs/2104.05915

Fast and precise single-cell data analysis using a hierarchical autoencoder.

Autoři: Tran, Duc Nguyen, Hung Tran, Bang a další

Zdroj: Nature Communications; 2/15/2021, Vol. 12 Issue 1, p1-10, 10p

Témata: CELL separation, RNA sequencing, DATA analysis, CELL analysis, GENES, MISSING data (Statistics)