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We introduce the use of autoregressive normalizing flows for rapid likelihood-free inference of binary black hole system parameters from gravitational-wave data with deep neural networks.
1903
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1903
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1908
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1909
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1909
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“Advanced LIGO anticipated sensitivity curves,” LIGO Technical Document, LIGO-T0900288-v2 (2009)
2009
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Qing Wang, Sanjeev R Kulkarni, and Sergio Verdú, “Divergence estimation for multidimensional densities via k k -nearest-neighbor distances,” IEEE Transactions on Information Theory 55
2009
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2013
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Daniel Foreman-Mackey, David W. Hogg, Dustin Lang, and Jonathan Goodman, “emcee: The MCMC Hammer,” Publications of the Astronomical Society of the Pacific 125
2013
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2014
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2014
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2015
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2015
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2015
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2016
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S. R. Hinton, “ChainConsumer,” The Journal of Open Source Software 1
2016
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Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning (MIT Press, 2016) http://www.deeplearningbook.org
2016
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2016
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2015
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J. Aasi et al. (LIGO Scientific), “Advanced LIGO,” Class. Quant. Grav. 32
2015
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2015
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2015
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2016
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2016
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2016
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2017
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Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala, “Pytorch: An imperative style, high-performance deep learning library,” in Advances in Neural Information Processing Systems 32 , edited by H. Wallach, H. Larochelle, A. Beygelzimer, F. d’Alché Buc, E. Fox, and R. Garnett (Curran Associates, Inc., 2019) pp. 8024–8035
2019
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Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, and Noah D. Goodman, “Pyro: Deep universal probabilistic programming,” J. Mach. Learn. Res. 20
2019
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