Functional autoencoder for smoothing and representation learning
From MaRDI portal
Publication:6657808
DOI10.1007/s11222-024-10501-wMaRDI QIDQ6657808
Sidi Wu, Cédric Beaulac, Jiguo Cao
Publication date: 7 January 2025
Published in: Statistics and Computing (Search for Journal in Brave)
Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10)
Cites Work
- Functional linear regression analysis for longitudinal data
- Nonlinear manifold representations for functional data
- Asymptotic theory for the principal component analysis of a vector random function: Some applications to statistical inference
- Sparse functional principal component analysis in a new regression framework
- Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions
- Density estimation by dual ascent of the log-likelihood
- Auto-association by multilayer perceptrons and singular value decomposition
- A simplified neuron model as a principal component analyzer
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Supervised functional principal component analysis
- Generalized functional linear models
- Functional data analysis.
- Nonparametric functional data analysis. Theory and practice.
- Nonlinear and additive principal component analysis for functional data
- Reducing the Dimensionality of Data with Neural Networks
- Functional mixture regression
- A Family of Nonparametric Density Estimation Algorithms
- Functional Clustering and Identifying Substructures of Longitudinal Data
- Recovering the underlying trajectory from sparse and irregular longitudinal data
- Functional principal component analysis estimator for non-Gaussian data
- Learning representations by back-propagating errors
- Localized Functional Principal Component Analysis
- Functional Additive Models
- On Properties of Functional Principal Components Analysis
- Functional Modelling and Classification of Longitudinal Data*
- Functional Data Analysis for Sparse Longitudinal Data
- Parametric Functional Principal Component Analysis
- Neural networks for scalar input and functional output
- The Elements of Statistical Learning
- Functional Nonlinear Learning
- Functional principal component analysis for longitudinal data with informative dropout
This page was built for publication: Functional autoencoder for smoothing and representation learning