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Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations

, , , and . (2019)cite arxiv:1905.07410Comment: 23 pages, 17 figures, submitted to ApJ.

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Measuring the thermal and ionization state of the low-$z$ IGM using likelihood free inference, , , , , , , , and . (2022)cite arxiv:2207.07151Comment: 20 pages, 17 figures, accepted for publication in MNRAS.Mining for strong gravitational lenses with self-supervised learning., , , , and . CoRR, (2021)Modeling the Lyman-$\alpha$ forest with Eulerian and SPH hydrodynamical methods, , , , , , , , and . (2022)cite arxiv:2207.05023Comment: submitted to MNRAS.The Lyman-$\alpha$ forest in optically-thin hydrodynamical simulations, , , , , and . (2014)cite arxiv:1406.6361Comment: 27 pages, 30 figures.Structure Finding in Cosmological Simulations: The State of Affairs, , , , , , , , , and 25 other author(s). (2013)cite arxiv:1304.0585Comment: 28 pages containing 11 figures & 4 tables + 9 pages appendix containing another 4 tables + 5 pages of references, submitted to MNRAS.A New Method to Measure the Post-Reionization Ionizing Background from the Joint Distribution of Lyman-$\alpha$ and Lyman-$\beta$ Forest Transmission, , , and . (2017)cite arxiv:1703.10174Comment: 15 pages, 18 figures, ApJ submitted.A Detection of $z$~2.3 Cosmic Voids from 3D Lyman-$\alpha$ Forest Tomography in the COSMOS Field, , , , , , , , , and 3 other author(s). (2017)cite arxiv:1710.02612Comment: 18 pages, 9 figures, to be submitted to ApJ.Nyx: A Massively Parallel AMR Code for Computational Cosmology., , , , , , and . J. Open Source Softw., 6 (63): 3068 (2021)Tuning Object-Centric Data Management Systems for Large Scale Scientific Applications., , , , , , and . HiPC, page 103-112. IEEE, (2019)Master of Puppets: Cooperative Multitasking for In Situ Processing., and . HPDC, page 285-288. ACM, (2016)