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The next generation 21 cm surveys open a new window onto the early stages of cosmic structure formation and provide new insights about the Epoch of Reionization (EoR).
Cosmology at low frequencies: The 21cm transition and the high-redshift universe
Steven R. Furlanetto, S. [Peng Oh], and Frank H. Briggs · 2006
Earlier work this paper cites.
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
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Cosmic reionization and the 21 cm signal: Comparison between an analytical model and a simulation
Mário G. Santos, Alexandre Amblard, Jonathan Pritchard, Hy Trac, Renyue Cen, and Asantha Cooray · 2008
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Practical variational inference for neural networks
Alex Graves · 2011
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21cmfast: a fast, seminumerical simulation of the high-redshift 21-cm signal
Andrei Mesinger, Steven Furlanetto, and Renyue Cen · 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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Bayesian convolutional neural networks with bernoulli approximate variational inference, 2015
Yarin Gal and Zoubin Ghahramani · 2015
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Dropout as a Bayesian approximation: Insights and applications
Yarin Gal and Zoubin Ghahramani · 2015
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Improved variational inference with inverse autoregressive flow
Durk P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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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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Masked autoregressive flow for density estimation
George Papamakarios, Theo Pavlakou, and Iain Murray · 2017
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On Calibration of Modern Neural Networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li and Yarin Gal · 2017
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Uncertainties in parameters estimated with neural networks: Application to strong gravitational lensing
Laurence Perreault Levasseur, Yashar D. Hezaveh, and Risa H. Wechsler · 2017
Cited alongside, same era.
Identifying reionization sources from 21cm maps using Convolutional Neural Networks
Sultan Hassan, Adrian Liu, Saul Kohn, and Paul La Plante · 2018
Cited alongside, same era.
Machine learning applied to the reionization history of the universe in the 21 cm signal
Paul La Plante and Michelle Ntampaka · 2019
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Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the ska, 2019
Sultan Hassan, Sambatra Andrianomena, and Caitlin Doughty · 2019
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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
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Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks
Hector J. Hortua, Riccardo Volpi, Dimitri Marinelli, and Luigi Malagò · 2019
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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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Conditional Density Estimation with Bayesian Normalising Flows
Brian L Trippe and Richard E Turner · 2018
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Chin-Wei Huang, David Krueger, Alexandre Lacoste, and Aaron Courville · 2018
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Neural ordinary differential equations
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Ffjord: Free-form continuous dynamics for scalable reversible generative models
Will Grathwohl, Ricky TQ Chen, Jesse Bettencourt, Ilya Sutskever, and David Duvenaud · 2018
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Flipout: Efficient pseudo-independent weight perturbations on mini-batches
Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, and Roger Grosse · 2018
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.
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan · 2019
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Normalizing flows: An introduction and review of current methods
Ivan Kobyzev, Simon Prince, and Marcus A Brubaker · 2019
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Extracting the 21 cm global signal using artificial neural networks
Madhurima Choudhury, Abhirup Datta, and Arnab Chakraborty · 2019
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Evaluating and calibrating uncertainty prediction in regression tasks
Dan Levi, Liran Gispan, Niv Giladi, and Ethan Fetaya · 2019
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GetDist: a Python package for analysing Monte Carlo samples
Antony Lewis · 2019
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Improving cosmological parameter estimation with the future 21 cm observation from ska
Jing-Fei Zhang, Li-Yang Gao, Dong-Ze He, and Xin Zhang · 2019
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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
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Parameters estimation from the 21 cm signal using variational inference, FSAI workshop, ICLR 2020
Héctor J. Hortúa, Riccardo Volpi, and Luigi Malagò · 2020
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