Amanote Research

Amanote Research

    RegisterSign In

A Transfer-Learning Approach to Feature Extraction From Cancer Transcriptomes With Deep Autoencoders

Lecture Notes in Computer Science - Germany
doi 10.1007/978-3-030-20521-8_74
Full Text
Open PDF
Abstract

Available in full text

Categories
Computer ScienceTheoretical Computer Science
Date

January 1, 2019

Authors
Guillermo López-GarcíaJosé M. JerezLeonardo FrancoFrancisco J. Veredas
Publisher

Springer International Publishing


Related search

Unsupervised Feature-Learning for Galaxy SEDs With Denoising Autoencoders

Astronomy and Astrophysics
AstrophysicsAstronomyPlanetary ScienceSpace
2017English

Fast Feedforward Non-Parametric Deep Learning Network With Automatic Feature Extraction

2017English

From Computer Supported Collaborative Learning to Deep Learning: A Systems Approach

SSRN Electronic Journal
2011English

An Efficient Approach to Informative Feature Extraction From Multimodal Data

Proceedings of the AAAI Conference on Artificial Intelligence
2019English

Clinical Relation Extraction With Deep Learning

International Journal of Hybrid Information Technology
Computer Science
2016English

A Generalized Approach to Linear Methods of Feature Extraction

1974English

A Deep Learning Approach to Identify Diabetes

2017English

An Evolutionary Method for Training Autoencoders for Deep Learning Networks

English

DeepTriangle: A Deep Learning Approach to Loss Reserving

Risks
ManagementFinanceEconomicsStrategyAccountingEconometrics
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy