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Upcoming experiments such as Hydrogen Epoch of Reionization Array (HERA) and Square Kilometre Array (SKA) are intended to measure the 21cm signal over a wide range of redshifts, representing an incredible opportunity in advancing our understanding about the nature of cosmic Reionization.
Cosmological parameter estimation using 21 cm radiation from the epoch of reionization
Matthew McQuinn, Oliver Zahn, Matias Zaldarriaga, Lars Hernquist, and Steven R. Furlanetto · 2006
Earlier work this paper cites.
Practical variational inference for neural networks
Alex Graves · 2011
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21 cm cosmology in the 21st century
Jonathan R Pritchard and Abraham Loeb · 2012
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21CMMC: an MCMC analysis tool enabling astrophysical parameter studies of the cosmic 21 cm signal
Bradley Greig and Andrei Mesinger · 2015
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What uncertainties do we need in bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal · 2017
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Structured uncertainty prediction networks
Garoe Dorta, Sara Vicente, Lourdes Agapito, Neill D. F. Campbell, and Ivor Simpson · 2018
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Identifying reionization sources from 21cm maps using Convolutional Neural Networks
Sultan Hassan, Adrian Liu, Saul Kohn, and Paul La Plante · 2018
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Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, and Roger Grosse · 2018
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An ensemble of bayesian neural networks for exoplanetary atmospheric retrieval
Adam D. Cobb, Michael D. Himes, Frank Soboczenski, Simone Zorzan, Molly D. O’Beirne, Atılım Güneş Baydin, Yarin Gal, Shawn D. Domagal-Goldman, Giada N. Arney, and Daniel Angerhausen and · 2019
Cited alongside, same era.
Deep learning from 21-cm tomography of the cosmic dawn and reionization
Nicolas Gillet, Andrei Mesinger, Bradley Greig, Adrian Liu, and Graziano Ucci · 2019
Cited alongside, same era.
Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the ska, 2019
Sultan Hassan, Sambatra Andrianomena, and Caitlin Doughty · 2019
Cited alongside, same era.
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks
Hector J. Hortua, Riccardo Volpi, Dimitri Marinelli, and Luigi Malagò · 2019
Later among the works it cites.
GetDist: a Python package for analysing Monte Carlo samples
Antony Lewis · 2019
Later among the works it cites.
Machine learning applied to the reionization history of the universe in the 21 cm signal
Paul La Plante and Michelle Ntampaka · 2019
Later among the works it cites.
Uncertainty quantification using bayesian neural networks in classification: Application to biomedical image segmentation
Yongchan Kwon, Joong-Ho Won, Beom Joon Kim, and Myunghee Cho Paik · 2020
Closest in time.
Uncertainties in parameters estimated with neural networks: Application to strong gravitational lensing
Laurence Perreault Levasseur, Yashar D. Hezaveh, and Risa H. Wechsler · 2041
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