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We present DE-VAE, a variational autoencoder (VAE) architecture to search for a compressed representation of dynamical dark energy (DE) models in observational studies of the cosmic large-scale structure.
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A. Lewis and A. Challinor, CAMB: Code for Anisotropies in the Microwave Background, Astrophysics Source Code Library, record ascl:1102.026 (2011), ascl:1102.026
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2017
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P. Ade, J. Aguirre, Z. Ahmed, S. Aiola, A. Ali, D. Alonso, M. A. Alvarez, K. Arnold, P. Ashton, J. Austermann, et al. , The Simons Observatory: science goals and forecasts, Journal of Cosmology and Astroparticle Physics 2019
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2012
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2012
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T. A. Wagner, S. Schlamminger, J. H. Gundlach, and E. G. Adelberger, Torsion-balance tests of the weak equivalence principle, Classical and Quantum Gravity 29
2012
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A. Hojjati, G.-B. Zhao, L. Pogosian, A. Silvestri, R. Crittenden, and K. Koyama, Cosmological tests of general relativity: A principal component analysis, Phys. Rev. D 85
2012
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2013
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S. Asaba, C. Hikage, K. Koyama, G.-B. Zhao, A. Hojjati, and L. Pogosian, Principal component analysis of modified gravity using weak lensing and peculiar velocity measurements, Journal of Cosmology and Astroparticle Physics 2013
2013
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2014
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M. D. Hoffman and A. Gelman, The no-u-turn sampler: Adaptively setting path lengths in hamiltonian monte carlo, J. Mach. Learn. Res. 15
2014
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2019
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2020
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S. K. N. Portillo, J. K. Parejko, J. R. Vergara, and A. J. Connolly, Dimensionality Reduction of SDSS Spectra with Variational Autoencoders, The Astronomical Journal 160
2020
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2020
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B. Bose, M. Cataneo, T. Tröster, Q. Xia, C. Heymans, and L. Lombriser, On the road to percent accuracy IV: ReACT – computing the non-linear power spectrum beyond Λ \Lambda CDM, Monthly Notices of the Royal Astronomical Society 498
2020
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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
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2021
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2021
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A. J. Mead, S. Brieden, T. Tröster, and C. Heymans, HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback, Monthly Notices of the Royal Astronomical Society 502
2021
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Euclid Collaboration, M. Knabenhans, J. Stadel, D. Potter, J. Dakin, S. Hannestad, T. Tram, S. Marelli, A. Schneider, R. Teyssier, et al. , Euclid preparation: IX. EuclidEmulator2 – power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations, Monthly Notices of the Royal Astronomical Society 505
2021
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S. G. Beauchamps, P. Baratta, J. Bel, S. Escoffier, and W. Gillard, Constraining the total neutrino mass with the power spectrum, Ateliers Dark Energy 1
2021
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2022
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M. Mancarella, J. Kennedy, B. Bose, and L. Lombriser, Seeking new physics in cosmology with bayesian neural networks: Dark energy and modified gravity, Phys. Rev. D 105
2022
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H. Teimoorinia, F. Archinuk, J. Woo, S. Shishehchi, and A. F. L. Bluck, Mapping the Diversity of Galaxy Spectra with Deep Unsupervised Machine Learning, The Astronomical Journal 163
2022
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L. Lucie-Smith, H. V. Peiris, A. Pontzen, B. Nord, J. Thiyagalingam, and D. Piras, Discovering the building blocks of dark matter halo density profiles with neural networks, Phys. Rev. D 105
2022
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A. Spurio Mancini, D. Piras, J. Alsing, B. Joachimi, and M. P. Hobson, CosmoPower: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys, Monthly Notices of the Royal Astronomical Society 511
2022
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2023
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B. Bose, M. Tsedrik, J. Kennedy, L. Lombriser, A. Pourtsidou, and A. Taylor, Fast and accurate predictions of the non-linear matter power spectrum for general models of Dark Energy and Modified Gravity, Monthly Notices of the Royal Astronomical Society 519
2023
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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, Machine Learning: Science and Technology 4
2023
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