Suchergebnisse - "Variational AutoEncoder"

DUALF-D: Disentangled dual-hyperprior approach for light field image compression

Autoren: Takhtardeshir, Soheib Olsson, Roger Guillemot, Christine et al.

Quelle: Signal processing. Image communication. 140

Schlagwörter: Light Field Compression, Variational Autoencoder, Disentanglement, Dual Hyperprior, Spatial-Angular Representation

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-55991
https://doi.org/10.1016/j.image.2025.117436

A supervised variational autoencoder framework for dimensionality reduction and predictive modeling in high-dimensional socioeconomic data

Autoren: Pei Xue Tianshun Li

Quelle: Journal of Economy and Technology, Vol 4, Iss, Pp 9-19 (2026)

Schlagwörter: High-dimensional data, Socioeconomic forecasting, Economics as a science, Electronic computers. Computer science, Supervised variational autoencoder, Social Sciences, QA75.5-76.95, Dimensionality reduction, HB71-74, Nonlinear representation learning, Predictive modeling

Zugangs-URL: https://doaj.org/article/38a6a8d09a8045ceaf6f58f757d3bf5e

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

Autoren: Martí Juan, Gerard

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

Thesis Advisors: Piella Fenoy, Gemma, Sanromà, Gerard

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: 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

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/671269

Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models

Autoren: Xiuxian Chen Guzhong Chen Kunchi Xie et al.

Quelle: Green Chemical Engineering, Vol 6, Iss 3, Pp 335-343 (2025)

Schlagwörter: Chemical engineering, Particle swarm optimization, Chemical space exploration, TP155-156, Variational autoencoder, QD415-436, CO2 solubility, Biochemistry, Ionic liquids

Zugangs-URL: https://doaj.org/article/ff42740a19f14b59a74b18f12f6c3097

SynapNet: A Complementary Learning System Inspired Algorithm With Real-Time Application in Multimodal Perception

Autoren: Nilay Kushawaha Lorenzo Fruzzetti Enrico Donato et al.

Quelle: IEEE Transactions on Neural Networks and Learning Systems. 36:13162-13176

Schlagwörter: Catastrophic forgetting, complementary learning system (CLS), continual learning (CL), perception, pseudo episodic memory, soft gripper, variational autoencoder (VAE)

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39190526

Optimal Dimensionality Reduction using Conditional Variational AutoEncoder

Autoren: Boussam, Sana Carbone, Mathieu Gérard, Benoît et al.

Weitere Verfasser: Boussam, Sana Carbone, Mathieu Gérard, Benoît et al.

Quelle: Transactions on Cryptographic Hardware and Embedded Systems, Vol 2025, Iss 3 (2025)

Schlagwörter: TK7885-7895, Computer engineering. Computer hardware, Deep Learning, Side-Channel Attacks, Variational AutoEncoder, Generative Models, Information technology, [INFO] Computer Science [cs], Optimal Dimensionality Reduction, T58.5-58.64, Optimal Attacks

Dateibeschreibung: application/pdf

Zugangs-URL: https://doaj.org/article/95892bfa2003433ea20557dbfd1de1dd
https://hal.science/hal-05148980v1
https://hal.science/hal-05148980v1/document
https://doi.org/10.46586/tches.v2025.i3.164-211

Disentangling Reasoning Factors for Natural Language Inference

Autoren: Xixi Zhou Limin Zeng Ziping Zhao et al.

Quelle: Big Data Mining and Analytics, Vol 8, Iss 3, Pp 694-711 (2025)

Schlagwörter: disentangled representation learning, Electronic computers. Computer science, natural language processing (nlp), variational autoencoder, QA75.5-76.95, natural language inference (nli)

Zugangs-URL: https://doaj.org/article/07249ebf86b947a598e55bda2c3c8dbd

AI-driven music composition: Melody generation using Recurrent Neural Networks and Variational Autoencoders

Autoren: Hanbing Zhao Siran Min Jianwei Fang et al.

Quelle: Alexandria Engineering Journal, Vol 120, Iss, Pp 258-270 (2025)

Schlagwörter: Recurrent neural network, Emotional expression, Variational autoencoder, Diversity and coherence, TA1-2040, Melody generation, Engineering (General). Civil engineering (General), Automated music composition

Zugangs-URL: https://doaj.org/article/14c612ce44984ac798a108bbf5a1ab2c

Data augmentation for damaged scenarios in floating offshore wind turbines: an approach based on diffusion architecture, hierarchical variational approximation and healthy data distribution

Autoren: Hamed Fathnejat Vincenzo Nava

Quelle: BIRD. BCAM's Institutional Repository Data
instname

Schlagwörter: Hierarchical variational autoencoder (HVAE), MNIST data augmentation, Floating offshore wind, Class imbalanced data, Diffusion process, Structural health monitoring (SHM)

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/20.500.11824/1982

Robust hierarchical anomaly detection using feature impact in IoT networks

Autoren: Joohong Rheey Hyunggon Park

Quelle: ICT Express, Vol 11, Iss 2, Pp 358-363 (2025)

Schlagwörter: Intrusion detection system, Adversarial attack, Anomaly detection, Variational autoencoder, Information technology, Feature impact, T58.5-58.64

Zugangs-URL: https://doaj.org/article/a95d02b4bbfa4b02aca72b4d2cbc1a1e

Using Variational Autoencoders for Out of Distribution Detection in Histological Multiple Instance Learning

Autoren: Francisco Javier Sáez-Maldonado Luz García Lee A. D. Cooper et al.

Quelle: Digibug. Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
IEEE Access, Vol 13, Pp 133351-133369 (2025)

Schlagwörter: Variational Autoencoder, multiple instance learning, Multiple instance learning, variational autoencoder, Electrical engineering. Electronics. Nuclear engineering, Out-of-distribution detection, TK1-9971

Zugangs-URL: https://doaj.org/article/d59532d3f27648c7acac265ee56ae2d6
https://hdl.handle.net/10481/106026

Exploring distribution learning of synthetic data generators

Autoren: Garg, Sonakshi Torra, Vicenç

Quelle: Computer Security. ESORICS 2024 International Workshops Lecture Notes in Computer Science. :65-76

Schlagwörter: Manifold Learning, Privacy, Synthetic Data Generators, Generative Adversarial Networks, Variational Autoencoder

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-238534

Enzyme sequence optimisation via Gromov-Wasserstein Autoencoders integrating MSA techniques

Autoren: Xuze Wang Yangyang Li Xiancong Hou et al.

Quelle: Journal of Enzyme Inhibition and Medicinal Chemistry, Vol 40, Iss 1 (2025)

Schlagwörter: representation learning, variational autoencoder, Therapeutics. Pharmacology, RM1-950, Enzyme optimisation

Zugangs-URL: https://doaj.org/article/16e87ee1e78943c7923a4c1ae167db11

A deep hybrid model for optimization of user preferences in marriage matching platforms

Autoren: Wenjuan Li Wen Fang Yahui Hu

Quelle: Alexandria Engineering Journal, Vol 133, Iss , Pp 1-12 (2025)

Schlagwörter: User preference modeling, Reinforcement learning, Variational autoencoder, Graph neural networks, Marriage matching platform, Personalized recommendation, Engineering (General). Civil engineering (General), TA1-2040

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1110016825010920; https://doaj.org/toc/1110-0168

Zugangs-URL: https://doaj.org/article/7b0a7db2b4f74f57bc23909143747bf1

scSpecies: enhancement of network architecture alignment in comparative single-cell studies

Autoren: Clemens Schächter Maren Hackenberg Martin Treppner et al.

Quelle: Genome Biology, Vol 26, Iss 1, Pp 1-27 (2025)

Schlagwörter: Cross-species alignment, Model organisms, Deep learning, Transfer learning, Variational autoencoder, Single-cell RNA sequencing, Biology (General), QH301-705.5, Genetics, QH426-470

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1474-760X

Zugangs-URL: https://doaj.org/article/4f906f16ba054640b15d1e1c62d34351

Fusion-aware quantum variational autoencoder for brain-heart signal modeling in mental health applications

Autoren: Ayesha Jabbar Huang Jianjun Muhammad Kashif Jabbar et al.

Quelle: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 9, Pp 1-21 (2025)

Schlagwörter: Quantum computing, Variational autoencoder, Brainwave recognition, Mental health, Internet of things, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Zugangs-URL: https://doaj.org/article/f87a6c5e49ce4ca892e29cdce81c4624

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

Unsupervised feature extraction using deep learning empowers discovery of genetic determinants of the electrocardiogram

Autoren: Ewa Sieliwonczyk Arunashis Sau Konstantinos Patlatzoglou et al.

Quelle: Genome Medicine, Vol 17, Iss 1, Pp 1-17 (2025)

Schlagwörter: GWAS, ECG, Deep learning, PheWAS, Burden testing, Variational autoencoder, Medicine, Genetics, QH426-470

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1756-994X

Zugangs-URL: https://doaj.org/article/ba09bf646fac473ca047d3a6f71ceb0d

Deep Unsupervised Learning for Condition Monitoring and Prediction of High Dimensional Data with Application on Windfarm SCADA Data

Autoren: Mylonas, Charilaos Abdallah, Imad Chatzi, Eleni et al.

Weitere Verfasser: Mylonas, Charilaos Abdallah, Imad Chatzi, Eleni et al.

Quelle: Model Validation and Uncertainty Quantification, Volume 3 ISBN: 9788743803522
Conference Proceedings of the Society for Experimental Mechanics Series
Model Validation and Uncertainty Quantification, Volume 3

Schlagwörter: Windfarm SCADA, DWM, 0202 electrical engineering, electronic engineering, information engineering, Uncertainty quantification, Deep learning, Variational autoencoder, 02 engineering and technology, 7. Clean energy

Dateibeschreibung: application/application/pdf

Zugangs-URL: https://www.research-collection.ethz.ch/bitstream/20.500.11850/496847/1/4586_myl.pdf
https://www.research-collection.ethz.ch/handle/20.500.11850/315814
https://link.springer.com/chapter/10.1007%2F978-3-030-12075-7_21
http://hdl.handle.net/20.500.11850/496847

Quantum Variational Autoencoder Based on Weak Measurements With Fuzzy Filtering of Input Data

Autoren: Vyacheslav Korolyov Maksim Ogurtsov Oleksandr Khodsinskyi

Quelle: Кібернетика та комп'ютерні технології, Iss 1, Pp 106-117 (2025)

Schlagwörter: neural network, weak measurements, Q300-390, variational autoencoder, fuzzy logic, Cybernetics, quantum computing

Zugangs-URL: https://doaj.org/article/e2bcdf8f56e649f69cdfca4e6ca97466