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Can small-scale baryon inhomogeneities resolve the Hubble tension? An investigation with ACT DR4

, , , , and . (2021)cite arxiv:2105.03003Comment: 10+2 pages, 6 figures.

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The CAMELS project: public data release., , , , , , , , , and 37 other author(s). CoRR, (2022)Can small-scale baryon inhomogeneities resolve the Hubble tension? An investigation with ACT DR4, , , , and . (2021)cite arxiv:2105.03003Comment: 10+2 pages, 6 figures.The Effective Geometry Monte Carlo Algorithm: Applications to Molecular Communication., , and . CoRR, (2018)Augmenting astrophysical scaling relations with machine learning : application to reducing the SZ flux-mass scatter., , , , , , , , , and . CoRR, (2022)The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence., , , , , , , , , and 18 other author(s). CoRR, (2021)Predicting the thermal Sunyaev-Zel'dovich field using modular and equivariant set-based neural networks., , , , and . Mach. Learn. Sci. Technol., 3 (3): 35002 (2022)Percent-level constraints on baryonic feedback with spectral distortion measurements, , , , , , , , , and . (2022)cite arxiv:2201.01663Comment: 10+5 pages, 7 figures.Effective Geometry Monte Carlo: A Fast and Reliable Simulation Framework for Molecular Communication., , and . IEEE Access, (2019)The SZ flux-mass (Y-M) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback., , , , , , , , , and 1 other author(s). CoRR, (2022)Multifield Cosmology with Artificial Intelligence., , , , , , , , , and 3 other author(s). CoRR, (2021)