Auto-association by multilayer perceptrons and singular value decomposition
about
Neural network models of categorical perceptionMathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural NetworksDL-PRO: A Novel Deep Learning Method for Protein Model Quality Assessment.Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5.Deep Learning in Medical Image Analysis.Shared acoustic codes underlie emotional communication in music and speech-Evidence from deep transfer learning.Neural network differentiation of optic neuritis and anterior ischaemic optic neuropathy.The divergent autoencoder (DIVA) model of category learning.Revealing unobserved factors underlying cortical activity with a rectified latent variable model applied to neural population recordings.Metrics for Performance Evaluation of Patient Exercises during Physical Therapy.Learning tactile skills through curious exploration.Complex-valued autoencoders.Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolutionUnsupervised learning of phase transitions: From principal component analysis to variational autoencoders.Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination.Unsupervised machine learning account of magnetic transitions in the Hubbard model.Deep Learning for Computer Vision: A Brief Review.Deep Learning and its Applications in Biomedicine.Singular value decomposition learning on double Stiefel manifold.Justifying and generalizing contrastive divergence.Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior.A First Application of Independent Component Analysis to Extracting Structure from Stock ReturnsNeural Networks and the Bias/Variance DilemmaPredicting drug resistance related to ABC transporters using unsupervised Consensus Self-Organizing MapsNeural Network Implementations for PCA and Its Extensions
P2860
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P2860
Auto-association by multilayer perceptrons and singular value decomposition
description
1988 nî lūn-bûn
@nan
1988 թուականին հրատարակուած գիտական յօդուած
@hyw
1988 թվականին հրատարակված գիտական հոդված
@hy
1988年の論文
@ja
1988年論文
@yue
1988年論文
@zh-hant
1988年論文
@zh-hk
1988年論文
@zh-mo
1988年論文
@zh-tw
1988年论文
@wuu
name
Auto-association by multilayer perceptrons and singular value decomposition
@ast
Auto-association by multilayer perceptrons and singular value decomposition
@en
Auto-association by multilayer perceptrons and singular value decomposition
@nl
type
label
Auto-association by multilayer perceptrons and singular value decomposition
@ast
Auto-association by multilayer perceptrons and singular value decomposition
@en
Auto-association by multilayer perceptrons and singular value decomposition
@nl
prefLabel
Auto-association by multilayer perceptrons and singular value decomposition
@ast
Auto-association by multilayer perceptrons and singular value decomposition
@en
Auto-association by multilayer perceptrons and singular value decomposition
@nl
P356
P1476
Auto-association by multilayer perceptrons and singular value decomposition
@en
P2093
P2888
P356
10.1007/BF00332918
P407
P577
1988-01-01T00:00:00Z
P6179
1044770331