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DISCO-DJ I: a differentiable Einstein-Boltzmann solver for cosmology

, , and . (2023)cite arxiv:2311.03291Comment: 29 pages, 8 figures, to be submitted to JCAP, comments very welcome.

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Formal upscaling and numerical validation of unsaturated flow models in fractured porous media., , , and . J. Comput. Phys., (2020)DISCO-DJ I: a differentiable Einstein-Boltzmann solver for cosmology, , and . (2023)cite arxiv:2311.03291Comment: 29 pages, 8 figures, to be submitted to JCAP, comments very welcome.The GCE in a New Light: Disentangling the γ-ray Sky with Bayesian Graph Convolutional Neural Networks., , , and . CoRR, (2020)Bayesian Simulation-based Inference for Cosmological Initial Conditions., , and . CoRR, (2023)A Novel Scheme for Dark Matter Annihilation Feedback in Cosmological Simulations, , , and . (2019)cite arxiv:1908.05812Comment: 18 pages, 10 (+2) figures.Rigorous Upscaling of Unsaturated Flow in Fractured Porous Media., , , and . SIAM J. Math. Anal., 52 (1): 239-276 (2020)A unified framework for 21cm tomography sample generation and parameter inference with Progressively Growing GANs., and . CoRR, (2020)Dim but not entirely dark: Extracting the Galactic Center Excess' source-count distribution with neural nets., , and . CoRR, (2021)Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models., , and . CoRR, (2023)A deep learning framework for jointly extracting spectra and source-count distributions in astronomy., , , and . CoRR, (2024)