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Ensemble averaging (machine learning)

Known as: Ensemble, Ensemble average (machine learning), Ensemble averaging 
In machine learning, particularly in the creation of artificial neural networks, ensemble averaging is the process of creating multiple models and… 
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Broader (1)

Artificial intelligence
Committee machineEnsemble learningGlossary of artificial intelligenceMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
An effective approach for software project effort and duration estimation with machine learning algorithms
Highly Cited
2015
Highly Cited
2015
The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing
The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models… 
Highly Cited
2014
Highly Cited
2014
Exploring EEG-based biometrics for user identification and authentication
As human brain activities, represented by EEG brainwave signals, are more confidential, sensitive, and hard to steal and… 
Highly Cited
2010
Highly Cited
2010
Upgrades to the reliability ensemble averaging method for producing probabilistic climate-change projections
We present an augmented version of the reliability ensemble averaging (REA) method designed to generate probabilistic climate… 
Review
2009
Review
2009
Fractal materials, beams, and fracture mechanics
Abstract.Continuing in the vein of a recently developed generalization of continuum thermomechanics, in this paper we extend… 
Highly Cited
2006
Highly Cited
2006
Ozone ensemble forecasts: 2. A Kalman filter predictor bias correction
[1] The Kalman filter (KF) is a recursive algorithm to estimate a signal from noisy measurements. In this study it is tested in… 
Highly Cited
2004
Highly Cited
2004
Diffuse interface modeling of two-phase flows based on averaging: mass and momentum equations
Highly Cited
2004
Highly Cited
2004
Uncertainties in Estimates of Reynolds Stress and TKE Production Rate Using the ADCP Variance Method
The use of acoustic Doppler current profilers (ADCPs) to measure turbulent parameters via the variance method involves… 
Highly Cited
2000
Highly Cited
2000
Cosserat modelling of size effects in the mechanical behaviour of polycrystals and multi-phase materials
Highly Cited
1990
Highly Cited
1990
Fermionic Molecular Dynamics
A new type of molecular dynamics us proposed to solved approximately the many-body problem of interacting identical fermions with… 
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