Publications

Christopher C. Lovell, Tjitske Starkenburg, Matthew Ho, Daniel Anglés-Alcázar, Romeel Davé, Austen Gabrielpillai, Kartheik Iyer, Alice E. Matthews, William J. Roper, Rachel Somerville, Laura Sommovigo, Francisco Villaescusa-Navarro (2024). Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours. arXiv e-prints.
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Chang-Goo Kim, Eve C. Ostriker, Jeong-Gyu Kim, Munan Gong, Greg L. Bryan, Drummond B. Fielding, Sultan Hassan, Matthew Ho, Sarah M.~R. Jeffreson, Rachel S. Somerville, Ulrich P. Steinwandel (2024). Metallicity Dependence of Pressure-regulated Feedback-modulated Star Formation in the TIGRESS-NCR Simulation Suite. apj.
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Shivam Pandey, Chirag Modi, Benjamin D. Wandelt, Deaglan J. Bartlett, Adrian E. Bayer, Greg L. Bryan, Matthew Ho, Guilhem Lavaux, T. Lucas Makinen, Francisco Villaescusa-Navarro (2024). CHARM: Creating Halos with Auto-Regressive Multi-stage networks. arXiv e-prints.
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Antoine Bourdin, Ronan Legin, Matthew Ho, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur (2024). Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics. arXiv e-prints.
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Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lazaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin Wandelt, Greg L. Bryan (2024). LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology. The Open Journal of Astrophysics.
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M. Ntampaka, M. Ho, B. Nord (2024). Building Trustworthy Machine Learning Models for Astronomy. Astromical Data Analysis Software and Systems XXXI.
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Ronan Legin, Matthew Ho, Pablo Lemos, Laurence Perreault-Levasseur, Shirley Ho, Yashar Hezaveh, Benjamin Wandelt (2024). Posterior sampling of the initial conditions of the universe from non-linear large scale structures using score-based generative models. mnras.
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R Legin, M Ho, P Lemos, Others (2024). MNRAS: Letters 527. L173.
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Matthew Ho, Xiaosheng Zhao, Benjamin Dan Wandelt (2024). Information-Ordered Bottlenecks for Adaptive Dimensionality Reduction.
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D. Huppenkothen, M. Ntampaka, M. Ho, M. Fouesneau, B. Nord, J.~E.~G. Peek, M. Walmsley, J.~F. Wu, C. Avestruz, T. Buck, M. Brescia, D.~P. Finkbeiner, A.~D. Goulding, T. Kacprzak, P. Melchior, M. Pasquato, N. Ramachandra, Y. -S. Ting, G. Van De Ven, S. Villar, V.~A. Villar, E. Zinger (2023). Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers. arXiv e-prints.
Cite DOI arXiv