Parameter estimation and model selection of gravitational wave signals contaminated by transient detector noise glitches

Jade Powell

doi:10.1088/1361-6382/aacf18

Parameter estimation and model selection of gravitational wave signals contaminated by transient detector noise glitches

Classical and Quantum Gravity ◽

10.1088/1361-6382/aacf18 ◽

2018 ◽

Vol 35 (15) ◽

pp. 155017 ◽

Cited By ~ 7

Author(s):

Jade Powell

Keyword(s):

Parameter Estimation ◽

Model Selection ◽

Gravitational Wave ◽

Detector Noise ◽

Selection Of

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An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models—Corrigendum

Publications of the Astronomical Society of Australia ◽

10.1017/pasa.2020.23 ◽

2020 ◽

Vol 37 ◽

Author(s):

Eric Thrane ◽

Colm Talbot

Keyword(s):

Parameter Estimation ◽

Bayesian Inference ◽

Model Selection ◽

Gravitational Wave ◽

Hierarchical Models ◽

Estimation Model

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Accelerated Bayesian model-selection and parameter-estimation in continuous gravitational-wave searches with pulsar-timing arrays

Physical Review D ◽

10.1103/physrevd.90.104028 ◽

2014 ◽

Vol 90 (10) ◽

Cited By ~ 18

Author(s):

Stephen Taylor ◽

Justin Ellis ◽

Jonathan Gair

Keyword(s):

Parameter Estimation ◽

Model Selection ◽

Gravitational Wave ◽

Bayesian Model ◽

Bayesian Model Selection ◽

Pulsar Timing

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Deep Learning Model Selection of Suboptimal Complexity

Автоматика и телемеханика ◽

10.31857/s000523100001252-1 ◽

2018 ◽

pp. 129-147

Author(s):

Oleg Bakhteev ◽

◽

Vadim Strijov ◽

Keyword(s):

Deep Learning ◽

Model Selection ◽

Learning Model ◽

Deep Learning Model ◽

Selection Of

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Model selection of extreme learning machine based on latent feature space

Journal of Computer Applications ◽

10.3724/sp.j.1087.2013.01600 ◽

2013 ◽

Vol 33 (6) ◽

pp. 1600-1603

Author(s):

Wentao MAO ◽

Zhongtang ZHAO ◽

Huanhuan HE

Keyword(s):

Model Selection ◽

Extreme Learning Machine ◽

Feature Space ◽

Learning Machine ◽

Selection Of

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An architecture for efficient gravitational wave parameter estimation with multimodal linear surrogate models

Classical and Quantum Gravity ◽

10.1088/1361-6382/aa7649 ◽

2017 ◽

Vol 34 (14) ◽

pp. 144002 ◽

Cited By ~ 10

Author(s):

Richard O’Shaughnessy ◽

Jonathan Blackman ◽

Scott E Field

Keyword(s):

Parameter Estimation ◽

Gravitational Wave ◽

Surrogate Models ◽

Wave Parameter

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Cosmological model selection from standard siren detections by third-generation gravitational wave observatories

Physics of the Dark Universe ◽

10.1016/j.dark.2021.100830 ◽

2021 ◽

Vol 32 ◽

pp. 100830

Author(s):

Josiel Mendonça Soares de Souza ◽

Riccardo Sturani

Keyword(s):

Model Selection ◽

Cosmological Model ◽

Gravitational Wave ◽

Third Generation

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886136 Determining soil hydraulic properties by parameter estimation: on the selection of a model for the hydraulic properties

International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts ◽

10.1016/0148-9062(88)91124-2 ◽

1988 ◽

Vol 25 (6) ◽

pp. 278

Keyword(s):

Parameter Estimation ◽

Hydraulic Properties ◽

Soil Hydraulic Properties ◽

Soil Hydraulic ◽

Selection Of

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A greedy algorithm for model selection of tensor decompositions

2013 IEEE International Conference on Acoustics, Speech and Signal Processing ◽

10.1109/icassp.2013.6638839 ◽

2013 ◽

Cited By ~ 2

Author(s):

Austin J. Brockmeier ◽

Jose C. Principe ◽

Anh Huy Phan ◽

Andrzej Cichocki

Keyword(s):

Model Selection ◽

Greedy Algorithm ◽

Tensor Decompositions ◽

Selection Of

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Joint Bayesian model selection and parameter estimation of the generalized extreme value model with covariates using birth-death Markov chain Monte Carlo

Water Resources Research ◽

10.1029/2007wr006427 ◽

2009 ◽

Vol 45 (6) ◽

Cited By ~ 28

Author(s):

Salaheddine El Adlouni ◽

Taha B. M. J. Ouarda

Keyword(s):

Monte Carlo ◽

Parameter Estimation ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Model Selection ◽

Bayesian Model ◽

Extreme Value ◽

Extreme Value Model ◽

Value Model ◽

Generalized Extreme Value Model

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Biases in parameter estimation from overlapping gravitational-wave signals in the third-generation detector era

Physical Review D ◽

10.1103/physrevd.104.044003 ◽

2021 ◽

Vol 104 (4) ◽

Author(s):

Anuradha Samajdar ◽

Justin Janquart ◽

Chris Van Den Broeck ◽

Tim Dietrich

Keyword(s):

Parameter Estimation ◽

Gravitational Wave ◽

Third Generation ◽

The Third

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