Suchergebnisse - Sparse Approximate Variational Autoencoder

No Reference Quality Assessment Metric for Multi-spectral and Multi-Modal Image Fusion using Sparse Approximate Variational Autoencoder

Autoren: Patil, Milind S. Mane, Pradip B.

Quelle: International Journal of Intelligent Systems and Applications in Engineering; Vol. 12 No. 17s (2024); 724-732

Schlagwörter: Deep Neural Network (DNN), Quality Assessment Regression Model, Sparse Approximate Variational Autoencoder

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.ijisae.org/index.php/IJISAE/article/view/4941

Advances in probabilistic modelling : sparse Gaussian processes, autoencoders, and few-shot learning

Autoren: Bauer, Matthias Rasmussen, Carl Edward Schölkopf, Bernhard

Weitere Verfasser: Bauer, Matthias Rasmussen, Carl Edward Schölkopf, Bernhard

Schlagwörter: 519.2, Machine Learning, Probabilistic Modelling, Gaussian Processes, Variational Autoencoders, Few-shot Learning, Meta-Learning, Transfer Learning, Approximate Bayesian Inference, Variational Inference, Inductive Biases, Amortised Inference, Sparse Gaussian Processes, Invariance

Zugangs-URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801859

Sparse-Coding Variational Autoencoders.

Autoren: Geadah, Victor Barello, Gabriel Greenidge, Daniel et al.

Quelle: Neural Computation. Dec2024, Vol. 36 Issue 12, p2571-2601. 31p.

Schlagwörter: *ARTIFICIAL neural networks, *VISUAL pathways, *NONLINEAR functions, *DATA modeling

Full-field expansion and damage detection from sparse measurements using physics-informed variational autoencoders.

Autoren: Kulkarni, Nitin Nagesh Sabato, Alessandro

Quelle: Structural Health Monitoring; Jan2026, Vol. 25 Issue 1, p607-629, 23p

Neutral Gas Phase Distribution from H I Morphology: Phase Separation with Scattering Spectra and Variational Autoencoders.

Autoren: Lei, Minjie Clark, S. E. Morel, Rudy et al.

Quelle: Astrophysical Journal; 2025, Vol. 993 Issue 1, p1-18, 18p

Schlagwörter: INTERSTELLAR medium, PHASE separation, HYDROGEN atom, SPECTRAL lines, SPATIAL arrangement, LATENT variables

Redefining Parameter Estimation and Covariate Selection via Variational Autoencoders: One Run Is All You Need.

Autoren: Rohleff J Bachmann F Nahum U et al.

Quelle: CPT: pharmacometrics & systems pharmacology [CPT Pharmacometrics Syst Pharmacol] 2025 Dec; Vol. 14 (12), pp. 2232-2243. Date of Electronic Publication: 2025 Nov 04.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Wiley Country of Publication: United States NLM ID: 101580011 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2163-8306 (Electronic) Linking ISSN: 21638306 NLM ISO Abbreviation: CPT Pharmacometrics Syst Pharmacol Subsets: MEDLINE

MeSH-Schlagworte: Artificial Intelligence*, Humans ; Bayes Theorem ; Nonlinear Dynamics ; Drug Development/methods ; Autoencoder

A variational autoencoder for probabilistic non-negative matrix factorisation.

Autoren: Squires, Steven Prügel Bennett, Adam Niranjan, Mahesan

Quelle: Pattern Analysis & Applications; Dec2025, Vol. 28 Issue 4, p1-10, 10p

Spatial-Frequency-Scale Variational Autoencoder for Enhanced Flow Diagnostics of Schlieren Data.

Autoren: Yang, Ronghua Wu, Hao Yang, Rongfei et al.

Quelle: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6233, 29p

Schlagwörter: FLUID dynamics, AUTOENCODERS, FLOW visualization, FOURIER transforms, DEEP learning, FEATURE extraction, FORECASTING

Accelerating the prediction of remanent polarization in multicomponent ferroelectrics by using variational autoencoder-based data augmentation.

Autoren: Sun, Zixiong Gao, Ruyue Wang, Ping et al.

Quelle: Journal of Materials Chemistry C; 8/28/2025, Vol. 13 Issue 32, p16551-16561, 11p

VAEMRS: Variational Autoencoder Based Movie Recommender System.

Autoren: Behera, Gopal Swain, Basanta Kumar Soni, Ravindra Kumar et al.

Quelle: Journal of Engineering Science & Technology Review; 2024, Vol. 17 Issue 6, p23-29, 7p

Schlagwörter: ARTIFICIAL neural networks, AUTOENCODERS, DEEP learning, PARAMETER estimation, BAYESIAN field theory, RECOMMENDER systems

Robust Multiple-Measurement Sparsity-Aware STAP with Bayesian Variational Autoencoder

Autoren: Chenxi Zhang Huiliang Zhao Wenchao Chen et al.

Quelle: Remote Sensing, Vol 14, Iss 15, p 3800 (2022)

Schlagwörter: clutter suppression, variational autoencoder (VAE), space−time adaptive processing (STAP), clutter plus noise covariance matrix (CCM), sparse recovery (SR), Science

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2072-4292/14/15/3800; https://doaj.org/toc/2072-4292

Zugangs-URL: https://doaj.org/article/c4b63c77f3634699bacdde42ee9d3496

Variational Autoencoder-Regulated Data Augmentation for Precise Estimation of Organic Pollutants in Water with Deeplearning Neural Network.

Autoren: Ashiquzzaman, Akm Kim, Jinsul Kim, Chihoon

Quelle: Applied Artificial Intelligence; Dec2025, Vol. 39 Issue 1, p1-12, 12p

Schlagwörter: DATA augmentation, DEEP learning, DISSOLVED organic matter, ENVIRONMENTAL monitoring, ORGANIC water pollutants, LIGHT absorbance, WATER quality

Personalized design aesthetic preference modeling: a variational autoencoder and meta-learning approach for multi-modal feature representation and transfer optimization.

Autoren: Chen, Chengliang Gong, Zhiqun

Quelle: Scientific Reports; 11/24/2025, Vol. 15 Issue 1, p1-19, 19p

Schlagwörter: AESTHETIC judgment, FEATURE extraction, CUSTOM design, KNOWLEDGE transfer, MACHINE learning

DMFVAE: miRNA-disease associations prediction based on deep matrix factorization method with variational autoencoder.

Autoren: Wei, Pijing Wang, Qianqian Gao, Zhen et al.

Quelle: Frontiers of Computer Science; Dec2024, Vol. 18 Issue 6, p1-12, 12p

Toward Accurate and Robust Pedestrian Detection via Variational Inference.

Autoren: He, Huanyu Lin, Weiyao Zhang, Yuang et al.

Quelle: International Journal of Computer Vision; Feb2025, Vol. 133 Issue 2, p867-889, 23p

Schlagwörter: MAXIMUM likelihood detection, MAXIMUM likelihood statistics, LATENT variables, AUTOENCODERS, DETECTORS, PEDESTRIANS

Transformer-variational autoencoder for estimating individual treatment effect using causal inference framework.

Autoren: Ahmad, Sohail Wang, Hong

Quelle: Applied Intelligence; Aug2025, Vol. 55 Issue 12, p1-16, 16p

Fault diagnosis using variational autoencoder GAN and focal loss CNN under unbalanced data.

Autoren: Li, Weihan Liu, Dunke Li, Yang et al.

Quelle: Structural Health Monitoring; May2025, Vol. 24 Issue 3, p1859-1872, 14p

Schlagwörter: CONVOLUTIONAL neural networks, GENERATIVE adversarial networks, FAULT diagnosis, AUTOENCODERS, GRAYSCALE model

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures.

Autoren: Lee, Guan-Wei Livadiotis, Stylianos Salamone, Salvatore

Quelle: Structural Health Monitoring; May2025, Vol. 24 Issue 3, p1601-1618, 18p

Schlagwörter: ACOUSTIC localization, AUTOENCODERS, LAMB waves, DEEP learning, FEATURE extraction

Improving Atmospheric Noise Correction from InSAR Time Series Using Variational Autoencoder with Clustering (VAE-Clustering) Method.

Autoren: Ghosh, Binayak Motagh, Mahdi Anvari, Mohammad Ali et al.

Quelle: Remote Sensing; Sep2025, Vol. 17 Issue 18, p3189, 27p

Schlagwörter: RADAR interferometry, SYNTHETIC aperture radar, CLUSTERING algorithms, ENVIRONMENTAL monitoring, ATMOSPHERIC acoustics, WEATHER, LATENT variables, GEOPHYSICAL observations

Geografische Kategorien: IRAN, MASHHAD (Iran)

PIGPVAE: physics-informed gaussian process variational autoencoders.

Autoren: Spitieris, Michail Ruocco, Massimiliano Murad, Abdulmajid et al.

Quelle: Applied Intelligence; Aug2025, Vol. 55 Issue 12, p1-16, 16p