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We propose a new model of Bayesian Neural Networks to not only detect the events of compact binary coalescence in the observational data of gravitational waves (GW) but also identify the full length of the event duration including the inspiral stage.
1901
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1901
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1901
Earlier work this paper cites.
1903
Earlier work this paper cites.
1903
Earlier work this paper cites.
1904
Earlier work this paper cites.
1908
Earlier work this paper cites.
1909
Earlier work this paper cites.
1910
Earlier work this paper cites.
S. Kullback and R. A. Leibler, On information and sufficiency, Ann. Math. Statist. 22
1951
Earlier work this paper cites.
D. E. Rumelhart, G. E. Hinton, and R. J. Williams, Learning representations by back-propagating errors, Nature 323
1986
Earlier work this paper cites.
L. E. Atlas, T. Homma, and R. J. M. II, An artificial neural network for spatio-temporal bipolar patterns: Application to phoneme classification, in Neural Information Processing Systems , edited by D. Z. Anderson (American Institute of Physics, 1988) pp. 31–40
1988
Earlier work this paper cites.
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, Backpropagation applied to handwritten zip code recognition, Neural Computation 1
1989
Earlier work this paper cites.
J. Hertz, A. Krogh, and R. G. Palmer, Introduction to the Theory of Neural Computation (Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1991)
1991
Earlier work this paper cites.
D. J. C. MacKay, A practical bayesian framework for backpropagation networks, Neural Comput. 4
1992
Earlier work this paper cites.
G. E. Hinton and R. M. Neal, Bayesian learning for neural networks (1995)
1995
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, Long short-term memory, Neural Computation 9
1997
Earlier work this paper cites.
S. Kullback, Information theory and statistics (Courier Corporation, 1997)
1997
Earlier work this paper cites.
B. J. Owen and B. S. Sathyaprakash, Matched filtering of gravitational waves from inspiraling compact binaries: Computational cost and template placement, Phys. Rev. D60
1999
Earlier work this paper cites.
M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, An introduction to variational methods for graphical models, Machine Learning 37
1999
Earlier work this paper cites.
M. Riesenhuber and T. Poggio, Hierarchical models of object recognition in cortex, Nature Neuroscience 2
1999
Earlier work this paper cites.
F. A. Gers, J. Schmidhuber, and F. Cummins, Learning to forget: Continual prediction with lstm, Neural Computation 12
2000
Earlier work this paper cites.
2001
Earlier work this paper cites.
2004
Earlier work this paper cites.
A. Niculescu-Mizil and R. Caruana, Predicting good probabilities with supervised learning, in ICML (2005)
2005
Earlier work this paper cites.
2006
Earlier work this paper cites.
2007
Earlier work this paper cites.
S. Klimenko, I. Yakushin, A. Mercer, and G. Mitselmakher, A coherent method for detection of gravitational wave bursts, Classical and Quantum Gravity 25
2008
Earlier work this paper cites.
2009
Cited alongside, same era.
2009
Cited alongside, same era.
V. Nair and G. E. Hinton, Rectified linear units improve restricted boltzmann machines, in ICML (2010)
2010
Cited alongside, same era.
B. Iyer, T. Souradeep, C. Unnikrishnan, S. Dhurandhar, S. Raja, and A. Sengupta, Ligo-india, proposal of the consortium for indian initiative in gravitational-wave observations (indigo) (2011), lIGO-M1100296-v2
2011
Cited alongside, same era.
A. Goldstein et al. , An ordinary short gamma-ray burst with extraordinary implications:fermi-GBM detection of GRB 170817a, The Astrophysical Journal 848
2017
Later among the works it cites.
V. Savchenko et al. , INTEGRALDetection of the first prompt gamma-ray signal coincident with the gravitational-wave event GW170817, The Astrophysical Journal 848
2017
Later among the works it cites.
2017
Later among the works it cites.
C. Pankow, L. Sampson, L. Perri, E. Chase, S. Coughlin, M. Zevin, and V. Kalogera, ASTROPHYSICAL PRIOR INFORMATION AND GRAVITATIONAL-WAVE PARAMETER ESTIMATION, The Astrophysical Journal 834
2017
Later among the works it cites.
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2011
Cited alongside, same era.
B. D. Metzger and E. Berger, WHAT IS THE MOST PROMISING ELECTROMAGNETIC COUNTERPART OF a NEUTRON STAR BINARY MERGER?, The Astrophysical Journal 746
2012
Cited alongside, same era.
2012
Cited alongside, same era.
2013
Cited alongside, same era.
2013
Cited alongside, same era.
F. Acernese et al. , Advanced virgo: a second-generation interferometric gravitational wave detector, Classical and Quantum Gravity 32
2014
Cited alongside, same era.
H. Sak, A. Senior, and F. Beaufays, Long short-term memory recurrent neural network architectures for large scale acoustic modeling, Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH , 338 (2014)
2014
Cited alongside, same era.
2014
Cited alongside, same era.
C. Messick, K. Blackburn, P. Brady, P. Brockill, K. Cannon, R. Cariou, S. Caudill, S. J. Chamberlin, J. D. E. Creighton, R. Everett, C. Hanna, D. Keppel, R. N. Lang, T. G. F. Li, D. Meacher, A. Nielsen, C. Pankow, S. Privitera, H. Qi, S. Sachdev, L. Sadeghian, L. Singer, E. G. Thomas, L. Wade, M. Wade, A. Weinstein, and K. Wiesner, Analysis framework for the prompt discovery of compact binary mergers in gravitational-wave data, Phys. Rev. D 95
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
A. Kendall and Y. Gal, What uncertainties do we need in bayesian deep learning for computer vision?, in Advances in Neural Information Processing Systems 30 , edited by I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Curran Associates, Inc., 2017) pp. 5574–5584
2017
Later among the works it cites.
T. Gebhard, N. Kilbertus, G. Parascandolo, I. Harry, and B. Schölkopf, Convwave: Searching for gravitational waves with fully convolutional neural nets, in Workshop on Deep Learning for Physical Sciences (DLPS) at the 31st Conference on Neural Information Processing Systems (2017)
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
Y. Kwon, J.-H. Won, B. J. Kim, and M. C. Paik, Uncertainty quantification using bayesian neural networks in classification: Application to ischemic stroke lesion segmentation (2018)
2018
Later among the works it cites.
LIGO Scientific Collaboration, LIGO Algorithm Library - LALSuite , free software (GPL) (2018)
2018
Later among the works it cites.
2018
Later among the works it cites.
N. Akhtar and A. Mian, Threat of adversarial attacks on deep learning in computer vision: A survey, IEEE Access 6
2018
Later among the works it cites.
2019
Later among the works it cites.
A. Nitz, I. Harry, D. Brown, C. M. Biwer, J. Willis, T. D. Canton, C. Capano, L. Pekowsky, T. Dent, A. R. Williamson, S. De, G. Davies, M. Cabero, D. Macleod, B. Machenschalk, S. Reyes, P. Kumar, T. Massinger, F. Pannarale, dfinstad, M. Tápai, S. Fairhurst, S. Khan, L. Singer, A. Nielsen, shasvath, S. Kumar, idorrington92, H. Gabbard, and B. U. V. Gadre, gwastro/pycbc: Pycbc release v1.15.2 (2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
G. Deodato, C. Ball, and X. Zhang, Bayesian neural networks for cellular image classification and uncertainty analysis, bioRxiv 10.1101/824862 (2019)
2019
Later among the works it cites.
R. Ormiston, T. Nguyen, M. Coughlin, R. X. Adhikari, and E. Katsavounidis, Noise reduction in gravitational-wave data via deep learning, Phys. Rev. Research 2
2020
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