MH

Matthew Ho

0000-0003-3207-8868

astro-ph.COastro-ph.GAastro-ph.IMcs.LGastro-ph.HEstat.MLhep-ph

On Valency

published · living versions

Celia: Catalog Embeddings Learned from cosmologIcal simulAtions

with Xiaowen Zhang, Anshul Kumar, Tiziana Di Matteo, Rupert A. C. Croft +1

1 version

W_bqnrtmgvv1 · current

Preprints & journals

33 papers in the corpus · 2019–2026

The Deep Learning Halo Definer: A Multimodal Framework for Halo Mass and Gas Fraction Inference on Galaxy Groups and Clusters

Caleb Ogle, Kalvyn N. Poncelet Adams, Benjamin D. Oppenheimer et al.

0 citations

2609.22543v12026arXiv

CNN-Based Inference of Gaseous Halo Properties from Synthetic X-ray and 21-cm HI Observations

Kalvyn N. Poncelet Adams, Benjamin D. Oppenheimer, Naomi Gluck et al.

0 citations

2609.16421v12026arXiv

Don't Cut Corners: How Training Outside the Prior Makes Simulation-Based Inference More Robust

Chaipat Tirapongprasert, Matthew Ho

0 citations

2608.12470v12026arXiv

DegenDetector: Symbolic Recovery of Parameter Degeneracies in Bayesian Posteriors

Chaipat Tirapongprasert, Matthew Ho

0 citations

2607.08755v12026arXiv

Cluster Mass Inference from Galaxy Kinematics

Bonny Y. Wang, Leander Thiele, Matthew Ho

0 citations

2606.12938v12026arXiv

Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations

Laura Sommovigo, Deaglan J. Bartlett, Rachel K. Cochrane et al.

0 citations

2606.10027v12026ApJ 1008 218 (2026)

Introducing sapphire: Towards Hybrid Physics-Informed, Data-Driven Modeling of Galaxy Formation

Viraj Pandya, Greg L. Bryan, T. Lucas Makinen et al.

0 citations

2604.06318v22026arXiv

Learning at the Edge: Tailed-Uniform Sampling for Robust Simulation-Based Inference

Chaipat Tirapongprasert, Matthew Ho

0 citations

2601.17120v22026arXiv

Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer

Thomas Harvey, Christopher C. Lovell, Sophie Newman et al.

2 citations

2511.10640v22025arXiv

Simulation-Based Inference for Direction Reconstruction of Ultra-High-Energy Cosmic Rays with Radio Arrays

Oscar Macias, Zachary Mason, Matthew Ho et al.

2 citations

2508.15991v22025arXiv

Cosmology with One Galaxy: Auto-Encoding the Galaxy Properties Manifold

Amanda Lue, Shy Genel, Marc Huertas-Company et al.

3 citations

2502.17568v22025The Astrophysical Journal, 986(2), 133 (June 2025)

Learning the Universe: physically-motivated priors for dust attenuation curves

Laura Sommovigo, Rachel K. Cochrane, Rachel S. Somerville et al.

13 citations

2502.13240v12025arXiv

Learning the Universe: $3\ h^{-1}{\rm Gpc}$ Tests of a Field Level $N$ -body Simulation Emulator

Matthew T. Scoggins, Matthew Ho, Francisco Villaescusa-Navarro et al.

0 citations

2502.13242v12025arXiv

RTFAST-Spectra: Emulation of X-ray reverberation mapping for active galactic nuclei

Benjamin Ricketts, Daniela Huppenkothen, Matteo Lucchini et al.

1 citation

2412.10131v22024arXiv

Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours

Christopher C. Lovell, Tjitske Starkenburg, Matthew Ho et al.

12 citations

2411.13960v22024Mon Not R Astron Soc (2025) 3949-3979

Reconstructing Galaxy Cluster Mass Maps using Score-based Generative Modeling

Alan Hsu, Matthew Ho, Joyce Lin et al.

1 citation

2410.02857v22024arXiv

CHARM: Creating Halos with Auto-Regressive Multi-stage networks

Shivam Pandey, Chirag Modi, Benjamin D. Wandelt et al.

1 citation

2409.09124v12024arXiv

Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics

Antoine Bourdin, Ronan Legin, Matthew Ho et al.

1 citation

2408.00839v12024arXiv

Metallicity Dependence of Pressure-Regulated Feedback-Modulated Star Formation in the TIGRESS-NCR Simulation Suite

Chang-Goo Kim, Eve C. Ostriker, Jeong-Gyu Kim et al.

21 citations

2405.19227v22024arXiv

Bye-bye, Local-in-matter-density Bias: The Statistics of the Halo Field Are Poorly Determined by the Local Mass Density

Deaglan J. Bartlett, Matthew Ho, Benjamin D. Wandelt

2 citations

2405.00635v32024ApJL 977 L44 (2024)

LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology

Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier et al.

36 citations

2402.05137v220242024 OJA, Vol. 7

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers

D. Huppenkothen, M. Ntampaka, M. Ho et al.

2 citations

2310.12528v12023arXiv

Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering

Chirag Modi, Shivam Pandey, Matthew Ho et al.

21 citations

2309.15071v12023arXiv

Information-Ordered Bottlenecks for Adaptive Semantic Compression

Matthew Ho, Xiaosheng Zhao, Benjamin Wandelt

1 citation

2305.11213v12023arXiv

Posterior Sampling of the Initial Conditions of the Universe from Non-linear Large Scale Structures using Score-Based Generative Models

Ronan Legin, Matthew Ho, Pablo Lemos et al.

25 citations

2304.03788v12023arXiv

Benchmarks and Explanations for Deep Learning Estimates of X-ray Galaxy Cluster Masses

Matthew Ho, John Soltis, Arya Farahi et al.

14 citations

2303.00005v220232023 MNRAS, 524, 3, 3289-3302

A Machine Learning Approach to Enhancing eROSITA Observations

John Soltis, Michelle Ntampaka, John Wu et al.

4 citations

2207.14324v22022arXiv

The Dynamical Mass of the Coma Cluster from Deep Learning

Matthew Ho, Michelle Ntampaka, Markus Michael Rau et al.

28 citations

2206.14834v12022arXiv

Building Trustworthy Machine Learning Models for Astronomy

Michelle Ntampaka, Matthew Ho, Brian Nord

1 citation

2111.14566v12021arXiv

CLMM: a LSST-DESC Cluster weak Lensing Mass Modeling library for cosmology

M. Aguena, C. Avestruz, C. Combet et al.

8 citations

2107.10857v22021arXiv

Approximate Bayesian Uncertainties on Deep Learning Dynamical Mass Estimates of Galaxy Clusters

Matthew Ho, Arya Farahi, Markus Michael Rau et al.

26 citations

2006.13231v220202021 ApJ, 908, 204H

Aging Halos: Implications of the Magnitude Gap on Conditional Statistics of Stellar and Gas Properties of Massive Halos

Arya Farahi, Matthew Ho, Hy Trac

24 citations

2001.05639v12020arXiv

A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters

Matthew Ho, Markus Michael Rau, Michelle Ntampaka et al.

86 citations

1902.05950v220192019 ApJ, 887, 25

Career total: 48 works. 33 are in this corpus.

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