Imperial College London

Luca Magri

Faculty of EngineeringDepartment of Aeronautics

Professor of Scientific Machine Learning
 
 
 
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Contact

 

l.magri Website

 
 
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Location

 

CAGB324City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Doan:2021,
author = {Doan, NAK and Polifke, W and Magri, L},
title = {Auto-Encoded Reservoir Computing for Turbulence Learning},
url = {http://arxiv.org/abs/2012.10968v2},
year = {2021}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - We present an Auto-Encoded Reservoir-Computing (AE-RC) approach to learn the dynamics of a 2D turbulent flow. The AE-RC consists of an Autoencoder, which discovers an efficient manifold representation of the flow state, and an Echo State Network, which learns the time evolution of the flow in the manifold. The AE-RC is able to both learn the time-accurate dynamics of the flow and predict its first-order statistical moments. The AE-RC approach opens up new possibilities for the spatio-temporal prediction of turbulence with machine learning.
AU - Doan,NAK
AU - Polifke,W
AU - Magri,L
PY - 2021///
TI - Auto-Encoded Reservoir Computing for Turbulence Learning
UR - http://arxiv.org/abs/2012.10968v2
ER -