Suchergebnisse - (conditional OR conditioning) variational autoencoder（cvae）

Conditional Variational Autoencoder (cVAE) for bio-plastic generation

Autoren: Choo, Hyunkyung Pakarinen, Olli Garg, Vikas Kumar

Zugangs-URL: https://cris.vtt.fi/en/publications/6296e553-af7a-49d8-a033-b2787f5771b6

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

Autoren: Alwani, Neil (author)

Index Begriffe: 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

Enhancing Global Surface Soil Moisture Estimation From ESA CCI and SMAP Product With a Conditional Variational Autoencoder

Autoren: Changjiang Shi Zhijie Zhang Shengqing Xiong et al.

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 9337-9359 (2024)

Schlagwörter: Conditional variational autoencoder (CVAE), SMAP L4, QC801-809, Geophysics. Cosmic physics, 0207 environmental engineering, 02 engineering and technology, 15. Life on land, surface soil moisture (SM), 01 natural sciences, Ocean engineering, product reconstruction, 13. Climate action, ESA climate change initiative (CCI), TC1501-1800, 0105 earth and related environmental sciences

Zugangs-URL: https://doaj.org/article/172f29a7106a48fb9baccd27a3d5514e

Physical discovery in representation learning via conditioning on prior knowledge.

Autoren: Liu, Yongtao Huey, Bryan D. Ziatdinov, Maxim A. et al.

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

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

Generating multiperspective process traces using conditional variational autoencoders

Autoren: Riccardo Graziosi Massimiliano Ronzani Andrei Buliga et al.

Quelle: Process Science. 2

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

Dateibeschreibung: application/pdf

Generative design of RHS/SHS profiles using Conditional Variational Autoencoder (CVAE)

Autoren: Müller, Andreas Kraus, Michael Anton Andras, Taras

Schlagwörter: CVAE, machine learning, local buckling, Digital design tools, high strength steel

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

Autoren: Cho, Wonwoong Chen, Yan-Ying Klenk, Matthew et al.

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

Zugangs-URL: http://arxiv.org/abs/2503.11937

Conditional variational autoencoders for generated hub genes in human endogenous retrovirus and periodontal inflammasome

Autoren: Pradeep Kumar Yadalam

Quelle: Gaceta Médica de Caracas. 133:709-714

Learning Conditional Variational Autoencoders with Missing Covariates

Autoren: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto et al.

Index Begriffe: Statistics - Machine Learning, Computer Science - Machine Learning, text

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

SpateCV: cross-modality alignment regularization of cell types improves spatial gene imputation for spatial transcriptomics

Autoren: Jiaqi Yuan Junhua Yu Qianbei Yi et al.

Quelle: Journal of Translational Medicine, Vol 23, Iss 1, Pp 1-21 (2025)

Schlagwörter: Spatial transcriptomics, Single-cell RNA sequencing, Gene imputation, Conditional variational autoencoder (CVAE), Attention mechanism, Medicine

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1479-5876

Zugangs-URL: https://doaj.org/article/a2b6ea14dfa84acc85be4d66915588f3

Survey on sampling conditioned brain images and imaging measures with generative models.

Autoren: Cheong, Sehyoung Lee, Hoseok Kim, Won Hwa

Quelle: Biomedical Engineering Letters; Sep2025, Vol. 15 Issue 5, p831-843, 13p

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

Autoren: Yuling Sang Abhirup Banerjee Marcel Beetz et al.

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

Schlagwörter: 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

Zugangs-URL: 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

Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder

Autoren: Jiang, Junhao Zuo, Yi Li, Zhiyuan

Quelle: Reliability Engineering and System Safety. 267

Schlagwörter: Graph convolutional network, Trajectory prediction, Cooperative intention constructor, Intelligent situational awareness systems, Conditional variational autoencoder, Multi-modal interaction extractor

Zugangs-URL: https://research.chalmers.se/publication/549377

Feasibility of Conditional Variational Autoencoders for Phase-Averaged Synthetic Time Series

Autoren: Rüb, Matthias Grüber, Jens Schotten, Hans D

Quelle: European Conference on Cyber Warfare and Security. 24:614-620

Aviation Fuel Pump Fault Diagnosis Based on Conditional Variational Self-Encoder Adaptive Synthetic Less Data Enhancement.

Autoren: Liu, Tiejun Zhang, Yaoping Yin, Xiaojing et al.

Quelle: Mathematics (2227-7390). Jul2025, Vol. 13 Issue 14, p2218. 18p.

Schlagwörter: *FUEL pumps, *FAULT diagnosis, *COMMERCIAL aeronautics, *MACHINE learning, *DATA augmentation

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

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

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

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

Learning conditional variational autoencoders with missing covariates

Autoren: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto et al.

Weitere Verfasser: Ramchandran, Siddharth Tikhonov, Gleb Lönnroth, Otto et al.

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

Dateibeschreibung: 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

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

Anomaly Detection for Charging Piles Based on Conditional Variational Autoencoder.

Autoren: Wang, Chuanjun Lu, Yinyu Wang, Mingxin et al.

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

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

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

Autoren: Chen, Jacky Hull, John Poulos, Zissis et al.

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

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

Generative Design of Thermoset Shape Memory Polymers Driven by Chemical Group: A Conditional Variational Autoencoder Approach

Autoren: Borun Das Andrew Peters Guoqiang Li et al.

Quelle: Journal of Polymer Science. 63:1334-1344