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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
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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.
2017
2017
Cell Detection with Deep Convolutional Neural Network and Compressed Sensing
Yao Xue
,
Nilanjan Ray
arXiv.org
2017
Corpus ID: 2523568
The ability to automatically detect certain types of cells or cellular subunits in microscopy images is of significant interest…
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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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2006
2006
Seasonal climate forecasts of the South Asian monsoon using multiple coupled models
T. N. Krishnamurti
,
A. Mitra
,
T. V. Vijaya Kumar
,
W. Yun
,
W. Dewar
2006
Corpus ID: 55588412
This study addresses seasonal climate forecasts using coupled atmosphere—ocean multimodels. Using as many as 67 different…
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2004
2004
An /spl epsiv/-margin nonlinear classifier based on fuzzy if-then rules
Jacek M. Łęski
IEEE Transactions on Systems, Man, and…
2004
Corpus ID: 6211767
This paper introduces a new classifier design methods that are based on a modification of the classical Ho-Kashyap procedure…
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2002
2002
Macrodispersivity for transport in arbitrary nonuniform flow fields: Asymptotic and preasymptotic results
I. Lunati
,
S. Attinger
,
W. Kinzelbach
2002
Corpus ID: 29166833
We use homogenization theory to investigate the asymptotic macrodispersion in arbitrary nonuniform velocity fields, which show…
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2001
2001
Higher-order spectra (HOS) invariants for shape recognition
Yuan Shao
,
M. Celenk
Pattern Recognition
2001
Corpus ID: 29583711
2000
2000
Uncertainty levels in predicted patterns of anthropogenic climate change
T. Barnett
,
G. Hegerl
,
T. Knutson
,
S. Tett
2000
Corpus ID: 9576053
This paper investigates the uncertainties in different model estimates of an expected anthropogenic signal in the near-surface…
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Highly Cited
1992
Highly Cited
1992
I2− photofragmentation/recombination dynamics in size‐selected I2−(CO2)n cluster ions: Observation of coherent I...I− vibrational motion
J. M. Papanikolas
,
V. Vorsa
,
M. Nadal
,
P. Campagnola
,
J. Gord
,
W. C. Lineberger
1992
Corpus ID: 29967702
We have employed picosecond pump–probe techniques in conjunction with a tandem time‐of‐flight mass spectrometer to investigate…
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1990
1990
Interpretation of cyclic flow variations in motored internal combustion engines
A. Enotiadis
,
C. Vafidis
,
J. Whitelaw
1990
Corpus ID: 78088299
Cyclic variations and turbulence characterisation are considered in the context of in-cylinder flows. Three methods of data…
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Review
1981
Review
1981
A posteriori time-varying filtering of averaged evoked potentials
J. P. C. de Weerd
Biological cybernetics
1981
Corpus ID: 25168997
This paper forms a preface and introduction to a new method for the estimation of evoked potentials: a posteriori time-varying…
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