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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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Related topics
Related topics
7 relations
Broader (1)
Artificial intelligence
Committee machine
Ensemble learning
Glossary of artificial intelligence
Machine learning
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing
J. Widlowski
,
Corrado Mio
,
+39 authors
T. Zenone
2015
Corpus ID: 27530695
The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models…
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Highly Cited
2014
Highly Cited
2014
Exploring EEG-based biometrics for user identification and authentication
Qiong Gui
,
Zhanpeng Jin
,
Wenyao Xu
IEEE Signal Processing in Medicine and Biology…
2014
Corpus ID: 14925689
As human brain activities, represented by EEG brainwave signals, are more confidential, sensitive, and hard to steal and…
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Highly Cited
2010
Highly Cited
2010
Upgrades to the reliability ensemble averaging method for producing probabilistic climate-change projections
Ying Xu
,
Xuejie Gao
,
F. Giorgi
2010
Corpus ID: 54813472
We present an augmented version of the reliability ensemble averaging (REA) method designed to generate probabilistic climate…
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Highly Cited
2010
Highly Cited
2010
The crossover from strong to weak chaos for nonlinear waves in disordered systems
T. Laptyeva
,
J. Bodyfelt
,
D. Krimer
,
C. Skokos
,
S. Flach
2010
Corpus ID: 118397177
We observe a crossover from strong to weak chaos in the spatiotemporal evolution of multiple-site excitations within disordered…
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Highly Cited
2004
Highly Cited
2004
Diffuse interface modeling of two-phase flows based on averaging: mass and momentum equations
Ying Sun
,
C. Beckermann
2004
Corpus ID: 39410848
Highly Cited
2004
Highly Cited
2004
Uncertainties in Estimates of Reynolds Stress and TKE Production Rate Using the ADCP Variance Method
E. Williams
,
J. Simpson
2004
Corpus ID: 73532649
The use of acoustic Doppler current profilers (ADCPs) to measure turbulent parameters via the variance method involves…
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Highly Cited
2003
Highly Cited
2003
Microrheology as a tool for high-throughput screening
V. Breedveld
,
D. Pine
2003
Corpus ID: 17791617
Microrheology can be used for high-throughput screening of the rheological properties of sample libraries of complex fluids. Two…
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Highly Cited
2000
Highly Cited
2000
Cosserat modelling of size effects in the mechanical behaviour of polycrystals and multi-phase materials
S. Forest
,
F. Barbe
,
G. Cailletaud
2000
Corpus ID: 54089482
Highly Cited
1990
Highly Cited
1990
Fermionic Molecular Dynamics
H. Feldmeier
,
J. Schnack
1990
Corpus ID: 11788387
A new type of molecular dynamics us proposed to solved approximately the many-body problem of interacting identical fermions with…
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Highly Cited
1990
Highly Cited
1990
An experimental study of a turbulent vortex ring
A. Glezer
,
D. Coles
Journal of Fluid Mechanics
1990
Corpus ID: 2649979
A turbulent vortex ring having a relatively thin core is formed in water by a momentary jet discharge from an orifice in a…
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