Výsledky vyhľadávania - (( conditional variational autoencoder（cvae） ) OR ( conditioning variational autoencoder（cvae） ))

A Variational Autoencoder Approach to Conditional Generation of Possible Future Volatility Surfaces.

Autori: Chen, Jacky Hull, John Poulos, Zissis a ďalší

Zdroj: Journal of Financial Data Science; Summer2025, Vol. 7 Issue 3, p86-114, 29p

Predmety: LONG short-term memory, PROBABILISTIC generative models, LATENT variables, RETROSPECTIVE studies, ECONOMIC forecasting

Synthetic data generation for the optimization of strains in metabolic engineering using latent space representations derived from a Conditional Variational Autoencoder

Autori: Alwani, Neil (author)

Témy: Metabolic Flux Analysis, Variational Autoencoder (VAE), Probabilistic analysis, Principal Component Analysis (PCA), Combinatorial Optimization, bachelor thesis

URL: http://resolver.tudelft.nl/uuid:0f0fbe65-257d-491d-9fe5-5c1b3864dfd4

Anomaly Detection for Charging Piles Based on Conditional Variational Autoencoder.

Autori: Wang, Chuanjun Lu, Yinyu Wang, Mingxin a ďalší

Zdroj: International Transactions on Electrical Energy Systems; 9/23/2025, Vol. 2025, p1-12, 12p

Predmety: ELECTRIC vehicles, SUPERVISED learning, PROBABILISTIC generative models, OUTLIER detection, SIGNAL detection, DISTRIBUTION (Probability theory), INFRASTRUCTURE (Economics)

Physical discovery in representation learning via conditioning on prior knowledge.

Autori: Liu, Yongtao Huey, Bryan D. Ziatdinov, Maxim A. a ďalší

Zdroj: Journal of Applied Physics; 8/14/2024, Vol. 136 Issue 6, p1-13, 13p

Predmety: PIEZORESPONSE force microscopy, SPECTRAL imaging, LATENT variables, EXTRAPOLATION, PRIOR learning

The Use of Conditional Variational Autoencoders in Generating Stellar Spectra.

Autori: Gebran, Marwan Bentley, Ian

Zdroj: Astronomy (2674-0346); Sep2025, Vol. 4 Issue 3, p13, 14p

Predmety: STELLAR spectra, RADIATIVE transfer, SIMULATION methods & models, SPECTRUM analysis, ASTROPHYSICS, PROBABILISTIC generative models, MACHINE learning, QUANTITATIVE research

Lightweight Text-to-Image Generation Model Based on Contrastive Language-Image Pre-Training Embeddings and Conditional Variational Autoencoders.

Autori: Wang, Yubo Zhang, Gaofeng

Zdroj: Electronics (2079-9292); Jun2025, Vol. 14 Issue 11, p2185, 31p

Predmety: AUTOENCODERS, SUPPLY & demand, GENERALIZATION

Generating multiperspective process traces using conditional variational autoencoders

Autori: Riccardo Graziosi Massimiliano Ronzani Andrei Buliga a ďalší

Zdroj: Process Science. 2

Predmety: Conditional models, Generative AI, Process mining, Deep learning

Popis súboru: application/pdf

Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder

Autori: Cho, Wonwoong Chen, Yan-Ying Klenk, Matthew a ďalší

Predmety: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Vision and Pattern Recognition

Prístupová URL adresa: http://arxiv.org/abs/2503.11937

Learning Conditional Variational Autoencoders with Missing Covariates

Autori: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto a ďalší

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

URL: http://arxiv.org/abs/2203.01218

Conditional VAE for personalized neurofeedback in cognitive training.

Autori: Tibermacine, Imad Eddine Russo, Samuele Scarano, Gianmarco a ďalší

Zdroj: PLoS ONE; 10/31/2025, Vol. 20 Issue 10, p1-28, 28p

Predmety: MACHINE learning, FEATURE extraction, NEUROPHYSIOLOGY, ARTIFICIAL intelligence, COGNITIVE training, ROUTINE diagnostic tests

Wind turbine structure health monitoring through zero-shot learning with supervised variational autoencoders

Autori: Kiran Bacsa

Zdroj: Materials Research Proceedings. 50:189-200

Deep conditional generative model for personalization of 12-lead electrocardiograms and cardiovascular risk prediction.

Autori: Sang, Yuling Banerjee, Abhirup Beetz, Marcel a ďalší

Zdroj: Frontiers in Digital Health; 2025, p1-13, 13p

Predmety: HEART anatomy, RISK assessment, PREDICTION models, RESEARCH funding, RECEIVER operating characteristic curves, CARDIOVASCULAR diseases risk factors, MAGNETIC resonance imaging, RELATIVE medical risk, ELECTROCARDIOGRAPHY, KAPLAN-Meier estimator, DEEP learning, SURVIVAL analysis (Biometry), ELECTRODES, PROPORTIONAL hazards models

Geografický termín: UNITED Kingdom

Map Completion Using Generative Models on a Custom Dataset.

Autori: Güzel, Selma Uslu, Erkan

Zdroj: Signal, Image & Video Processing; Nov2025, Vol. 19 Issue 11, p1-8, 8p

Deep conditional generative model for personalization of 12-lead electrocardiograms and cardiovascular risk prediction

Autori: Yuling Sang Abhirup Banerjee Marcel Beetz a ďalší

Zdroj: Front Digit Health
Frontiers in Digital Health, Vol 7 (2025)

Predmety: cardiovascular disease, ECG electrodes, Electronic computers. Computer science, cardiac MRI, cardiovascular risk prediction, Medicine, Digital Health, variational autoencoder, QA75.5-76.95, Public aspects of medicine, RA1-1270, ECG generation

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40309320
https://doaj.org/article/2a10921b18e7497d98cab78e66c9b407
https://ora.ox.ac.uk/objects/uuid:e5ae4f89-fe9e-4dee-b8f3-051c410e9671
https://doi.org/10.3389/fdgth.2025.1558589

Integrating cross-sample and cross-modal data for spatial transcriptomics and metabolomics with SpatialMETA.

Autori: Tian, Ruonan Xue, Ziwei Chen, Yiru a ďalší

Zdroj: Nature Communications; 10/6/2025, Vol. 16 Issue 1, p1-16, 16p

Predmety: METABOLOMICS, DATA integration, CANCER treatment, DATA harmonization, LATENT variables, MULTIOMICS, RNA sequencing

Learning conditional variational autoencoders with missing covariates

Autori: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto a ďalší

Prispievatelia: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto a ďalší

Predmety: Conditional VAEs, Gaussian process, Missing value imputation, Variational autoencoders, Computer and information sciences

Popis súboru: application/pdf

Relation: We would like to acknowledge the computational resources provided by Aalto Science-IT, Finland. We would also like to thank Mine Ogretir for help with the PPMI dataset as well as Manuel Haussmann for the helpful discussions and comments. This work was supported by the Academy of Finland [328401] and Bayer Oy. The PPMI dataset used in the preparation of this article was obtained from the Parkin-son's Progression Markers Initiative (PPMI) database (https://www.ppmi-info.org/access-data-specimens/download-data). For up-to-date information on the study, visit www.ppmi-info.org. PPMI - a public-private partnership - is funded by The Michael J. Fox Foundation for Parkinson's Research and funding partners, including 4D Pharma, AbbVie Inc., AcureX Therapeutics, Allergan, Amathus Therapeutics, Aligning Science Across Parkinson's (ASAP), Avid Radiopharmaceuticals, Bial Biotech, Biogen, BioLegend, Bristol Myers Squibb, CalicoLife Sciences LLC, Celgene Corporation, DaCapo Brainscience, Denali Therapeutics, The Edmond J. Safra Foundation, Eli Lilly and Company,GE Healthcare, GlaxoSmithKline, Golub Capital, Handl Therapeutics, Insitro, Janssen Pharmaceuticals, Lundbeck, Merck & Co., Inc., MesoScale Diagnostics, LLC, Neurocrine Biosciences, Pfizer Inc., Piramal Imaging, Prevail Therapeutics, F. Hoffmann-La Roche Ltd and its affiliated company Genentech Inc., Sanofi Genzyme, Servier, Takeda Pharmaceutical Company, Teva Neuroscience, Inc., UCB, Vanqua Bio, VerilyLife Sciences, Voyager Therapeutics, Inc., Yumanity Therapeutics, Inc.; Ramchandran , S , Tikhonov , G , Lönnroth , O , Tiikkainen , P & Lahdesmaki , H 2024 , ' Learning conditional variational autoencoders with missing covariates ' , Pattern Recognition , vol. 147 , 110113 . https://doi.org/10.1016/j.patcog.2023.110113; http://hdl.handle.net/10138/569684; 85177739591; 001124231300001

Dostupnosť: http://hdl.handle.net/10138/569684

MCVAE: A New Multi-Conditional Approach for Scalable Emergency Ad Hoc Network Design and Node Localization Using Generative Variational Autoencoder.

Autori: Jabbar, M. A. A. Abbas, A. R. Ghani, R. F.

Zdroj: International Journal of Engineering Transactions C: Aspects; Jun2026, Vol. 39 Issue 6, p1390-1401, 12p

Predmety: AD hoc computer networks, EMERGENCY management, REAL-time computing, AUTOENCODERS, PROBABILISTIC generative models, WIRELESS communications, SCALABILITY

Rapid Generation of Kilonova Light Curves Using Conditional Variational Autoencoder.

Autori: Saha, Surojit Williams, Michael J. Datrier, Laurence a ďalší

Zdroj: Astrophysical Journal; 2/1/2024, Vol. 961 Issue 2, p1-14, 14p

Predmety: LIGHT curves, STELLAR mergers, NEUTRON stars, BINARY stars, EQUATIONS of state

Learning conditional variational autoencoders with missing covariates

Autori: Tikhonov, Gleb Lönnroth, Otto Tiikkainen, Pekka a ďalší

Prispievatelia: Tikhonov, Gleb Lönnroth, Otto Tiikkainen, Pekka a ďalší

Zdroj: Pattern Recognition. 147:110113

Predmety: ta113, FOS: Computer and information sciences, Computer Science - Machine Learning, Conditional VAEs, Computer and information sciences, Missing value imputation, Machine Learning (stat.ML), 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG), Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Gaussian process, Variational autoencoders, 0105 earth and related environmental sciences

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2203.01218
http://juuli.fi/Record/0677962223
https://doi.org/10.1016/j.patcog.2023.110113
http://hdl.handle.net/10138/569684
https://aaltodoc.aalto.fi/handle/123456789/124762

PREmbed: Balancing Conditional Generative Models with Embedding Pretraining and Regularization.

Autori: Liu, Haiyang Endo, Yuki Lee, Jinho a ďalší

Zdroj: Electronics (2079-9292); Jan2025, Vol. 14 Issue 2, p280, 23p

Predmety: AUTOENCODERS, MOTIVATION (Psychology)