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Finding the best parametrization for cosmological models in the absence of first-principle theories is an open question.
1907
Earlier work this paper cites.
1908
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1909
Earlier work this paper cites.
S. Kullback and R. A. Leibler, On Information and Sufficiency, The Annals of Mathematical Statistics 22
1951
Earlier work this paper cites.
G. E. Hinton and R. S. Zemel, Autoencoders, Minimum Description Length and Helmholtz Free Energy, in NIPS (1993)
1993
Earlier work this paper cites.
W. Hu, M. Fukugita, M. Zaldarriaga, and M. Tegmark, Cosmic microwave background observables and their cosmological implications, The Astrophysical Journal 549
2001
Earlier work this paper cites.
A. Kosowsky, M. Milosavljevic, and R. Jimenez, Efficient cosmological parameter estimation from microwave background anisotropies, Phys. Rev. D 66
2002
Earlier work this paper cites.
2002
Earlier work this paper cites.
D. Huterer and G. Starkman, Parameterization of dark-energy properties: A Principal-component approach, Phys. Rev. Lett. 90
2003
Earlier work this paper cites.
2003
Earlier work this paper cites.
R. Jimenez, L. Verde, H. Peiris, and A. Kosowsky, Fast cosmological parameter estimation from microwave background temperature and polarization power spectra, Phys. Rev. D 70
2004
Earlier work this paper cites.
2006
Earlier work this paper cites.
2006
Earlier work this paper cites.
2006
Earlier work this paper cites.
2007
Earlier work this paper cites.
2008
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2009
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2009
Earlier work this paper cites.
2009
Earlier work this paper cites.
2009
Earlier work this paper cites.
2011
Earlier work this paper cites.
D. Blas, J. Lesgourgues, and T. Tram, The Cosmic Linear Anisotropy Solving System (CLASS). Part II: Approximation schemes, Journal of Cosmology and Astroparticle Physics 2011
2011
Earlier work this paper cites.
2012
Earlier work this paper cites.
D. Foreman-Mackey, D. W. Hogg, D. Lang, and J. Goodman, emcee: The MCMC Hammer, Publications of the Astronomical Society of the Pacific 125
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
D. J. Rezende, S. Mohamed, and D. Wierstra, Stochastic backpropagation and approximate inference in deep generative models, in International conference on machine learning (PMLR, 2014) pp. 1278–1286
2014
Cited alongside, same era.
2015
Cited alongside, same era.
S. Ioffe and C. Szegedy, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift, in Proceedings of the 32nd International Conference on Machine Learning , Proceedings of Machine Learning Research, Vol. 37, edited by F. Bach and D. Blei (PMLR, Lille, France, 2015) pp. 448–456
2015
Cited alongside, same era.
2023
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2023
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2023
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2015
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2016
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I. Higgins, L. Matthey, A. Pal, C. P. Burgess, X. Glorot, M. M. Botvinick, S. Mohamed, and A. Lerchner, beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework, in 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings (OpenReview.net, 2017)
2017
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2017
Cited alongside, same era.
2018
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2019
Cited alongside, same era.
2019
Cited alongside, same era.
E. Komatsu, Cosmic Microwave Background (Nippon Hyoronsha, Tokyo, 2019)
2019
Cited alongside, same era.
J. Alsing, H. Peiris, J. Leja, C. Hahn, R. Tojeiro, D. Mortlock, B. Leistedt, B. D. Johnson, and C. Conroy, SPECULATOR: Emulating Stellar Population Synthesis for Fast and Accurate Galaxy Spectra and Photometry, The Astrophysical Journal Supplement Series 249
2020
Cited alongside, same era.
2023
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2023
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D. Piras, H. V. Peiris, A. Pontzen, L. Lucie-Smith, N. Guo, and B. Nord, A robust estimator of mutual information for deep learning interpretability, Mach. Learn.: Sci. Technol. 4
2023
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2023
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2023
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2023
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2024
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2024
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2024
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N. Guo, L. Lucie-Smith, H. V. Peiris, A. Pontzen, and D. Piras, Deep learning insights into non-universality in the halo mass function, Monthly Notices of the Royal Astronomical Society 532
2024
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2024
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