JW
John F. Wu
astro-ph.GAastro-ph.IMastro-ph.COcs.LGastro-ph.HEcs.AIcs.IRastro-ph.SRcs.CVcs.DL
On Valency
published · living versionsW_gkxhbc4a·v1 · currentpublished
Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program
with Elise Darragh-Ford, Yao-Yuan Mao, Risa H. Wechsler, Marla Geha +37
1 version
W_tvq7fh49·v1published
Preprints & journals
46 papers in the corpus · 2014–2026Deep Learning for Astrophysics: An Open Textbook from the NASA Cosmic Origins AI/ML Science and Technology Interest Group2606.30855v2 · Yuan-Sen Ting, Digvijay Wadekar, Phill Cargile et al.2026 · 0 citationsarXiv
To What Extent Are Star Cluster Ages Encoded in Their Environments? Exploring the Spatial Distribution of Age-Related Information with PHANGS-HST Imaging and Convolutional Neural Networks2603.07289v1 · Javier Viana, Janice C. Lee, Andrew Vanderburg et al.2026 · 0 citationsarXiv
Improving Posterior Inference of Galaxy Properties with Image-Based Conditional Flow Matching2512.05078v1 · Mikaeel Yunus, John F. Wu, Benne W. Holwerda2025 · 0 citationsarXiv
The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters2510.09748v1 · Michelle Ntampaka, A. Ciprijanovic, Ana Maria Delgado et al.2025 · 0 citationsarXiv
The SAGA Survey. VI. The Size-Mass Relation for Low-Mass Galaxies Across Environments2509.25335v1 · Yasmeen Asali, Marla Geha, Erin Kado-Fong et al.2025 · 5 citationsarXiv
How does feedback affect the star formation histories of galaxies?2508.21152v1 · Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan et al.2025 · 7 citationsarXiv
Insights on Galaxy Evolution from Interpretable Sparse Feature Networks2501.00089v1 · John F. Wu2024 · 2 citationsApJ (2025), 980 183
Looking At the Distant Universe with the MeerKAT Array: the HI Mass Function in the Local Universe2412.11426v1 · Amir Kazemi-Moridani, Andrew J. Baker, Marc Verheijen et al.2024 · 2 citationsarXiv
Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks2411.12629v1 · Nikhil Garuda, John F. Wu, Dylan Nelson et al.2024 · 0 citationsarXiv
Basic Data Processing of Gravitational Waves2410.11858v2 · Jingxu Wu, YuWei Yin, Chenjia Li et al.2024 · 0 citationsarXiv
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy2408.01556v1 · Kartheik G. Iyer, Mikaeel Yunus, Charles O'Neill et al.2024 · 15 citationsarXiv
Disentangling Dense Embeddings with Sparse Autoencoders2408.00657v2 · Charles O'Neill, Christine Ye, Kartheik Iyer et al.2024 · 3 citationsarXiv
Predicting dark matter halo masses from simulated galaxy images and environments2407.13735v1 · Austin J. Larson, John F. Wu, Craig Jones2024 · 0 citationsarXiv
ALMA Lensing Cluster Survey: Physical characterization of near-infrared-dark intrinsically faint ALMA sources at z=2-42406.09890v2 · Akiyoshi Tsujita, Kotaro Kohno, Shuo Huang et al.2024 · 2 citationsarXiv
Designing an Evaluation Framework for Large Language Models in Astronomy Research2405.20389v1 · John F. Wu, Alina Hyk, Kiera McCormick et al.2024 · 0 citationsarXiv
The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way-mass Galaxies2404.14498v3 · Yao-Yuan Mao, Marla Geha, Risa H. Wechsler et al.2024 · 49 citationsAstrophysical Journal 976 (2024) 117
The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way-mass Galaxies2404.14499v2 · Marla Geha, Yao-Yuan Mao, Risa H. Wechsler et al.2024 · 30 citationsAstrophysical Journal 976 (2024) 118
The SAGA Survey. V. Modeling Satellite Systems around Milky Way-mass Galaxies with Updated UniverseMachine2404.14500v3 · Yunchong Wang, Ethan O. Nadler, Yao-Yuan Mao et al.2024 · 18 citationsThe Astrophysical Journal, Volume 976, Number 1, 119, 2024
Katachi: Decoding the Imprints of Past Star Formation on Present Day Morphology in Galaxies with Interpretable CNNs2404.05146v1 · Juan Pablo Alfonzo, Kartheik G. Iyer, Masayuki Akiyama et al.2024 · 0 citationsarXiv
How the Galaxy-Halo Connection Depends on Large-Scale Environment2402.07995v2 · John F. Wu, Christian Kragh Jespersen, Risa H. Wechsler2024 · 15 citationsarXiv
PHANGS-ML: dissecting multiphase gas and dust in nearby galaxies using machine learning2402.04330v1 · Dalya Baron, Karin M. Sandstrom, Erik Rosolowsky et al.2024 · 17 citationsarXiv
Deep Learning Cosmic Ray Transport from Density Maps of Simulated, Turbulent Gas2402.03518v1 · Chad Bustard, John Wu2024 · 0 citationsarXiv
A dark siren measurement of the Hubble constant using gravitational wave events from the first three LIGO/Virgo observing runs and DELVE2310.13695v2 · V. Alfradique, C. R. Bom, A. Palmese et al.2023 · 33 citationsarXiv
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers2310.12528v1 · D. Huppenkothen, M. Ntampaka, M. Ho et al.2023 · 2 citationsarXiv
Quantifying Roman WFI Dark Images with the Wavelet Scattering Transform2308.02028v1 · Phani Datta Velicheti, John F. Wu, Andreea Petric2023 · 1 citationPublications of the Astronomical Society of the Pacific (2023) 135, 1050
Learning the galaxy-environment connection with graph neural networks2306.12327v1 · John F. Wu, Christian Kragh Jespersen2023 · 3 citationsarXiv
NANCY: Next-generation All-sky Near-infrared Community surveY2306.11784v1 · Jiwon Jesse Han, Arjun Dey, Adrian M. Price-Whelan et al.2023 · 2 citationsarXiv
JWST constraints on the UV luminosity density at cosmic dawn: implications for 21-cm cosmology2305.02703v2 · Sultan Hassan, Christopher C. Lovell, Piero Madau et al.2023 · 16 citationsarXiv
A variable active galactic nucleus at triply-imaged by the galaxy cluster MACS J0035.4-20152303.00025v4 · Lukas J. Furtak, Ramesh Mainali, Adi Zitrin et al.2023 · 8 citationsarXiv
Identification of galaxy shreds in large photometric catalogs using Convolutional Neural Networks2301.09648v1 · Enrico M. Di Teodoro, Josh E. G. Peek, John F. Wu2023 · 3 citationsarXivon Valency
Identifying AGN host galaxies with convolutional neural networks2212.07881v1 · Ziting Guo, John F. Wu, Chelsea E. Sharon2022 · 0 citationsarXiv
Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program2212.07433v2 · Elise Darragh-Ford, John F. Wu, Yao-Yuan Mao et al.2022 · 33 citationsarXivon Valency
Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning2210.10802v3 · E. A. Zaborowski, A. Drlica-Wagner, F. Ashmead et al.2022 · 19 citationsApJ 954 68 (2023)
A Machine Learning Approach to Enhancing eROSITA Observations2207.14324v2 · John Soltis, Michelle Ntampaka, John Wu et al.2022 · 4 citationsarXiv
LADUMA: Discovery of a luminous OH megamaser at 2204.02523v1 · Marcin Glowacki, Jordan D. Collier, Amir Kazemi-Moridani et al.2022 · 12 citationsarXiv
The DECam Local Volume Exploration Survey Data Release 22203.16565v1 · A. Drlica-Wagner, P. S. Ferguson, M. Adam'ow et al.2022 · 79 citationsarXiv
Extending the SAGA Survey (xSAGA) I: Satellite Radial Profiles as a Function of Host Galaxy Properties2112.01542v2 · John F. Wu, J. E. G. Peek, Erik J. Tollerud et al.2021 · 25 citationsApJ (2022), 927, 121
Predicting the spectrum of UGC 2885, Rubin's Galaxy with machine learning2105.03377v1 · Benne W. Holwerda, John F. Wu, JHU et al.2021 · 14 citationsarXiv
Predicting galaxy spectra from images with hybrid convolutional neural networks2009.12318v2 · John F. Wu, J. E. G. Peek2020 · 8 citationsarXiv
ALMA Lensing Cluster Survey: an ALMA galaxy signposting a MUSE galaxy group at z=4.3 behind 'El Gordo'2009.04838v2 · K. I. Caputi, G. B. Caminha, S. Fujimoto et al.2020 · 39 citationsarXiv
Connecting optical morphology, environment, and HI mass fraction for low-redshift galaxies using deep learning2001.00018v2 · John F. Wu2019 · 18 citations2020, ApJ, 900, 148
The Star-Forming Interstellar Medium of Lyman Break Galaxy Analogs1911.07854v1 · John F. Wu, Andrew J. Baker, Timothy M. Heckman et al.2019 · 9 citations2019, ApJ, 887, 251
Using convolutional neural networks to predict galaxy metallicity from three-color images1810.12913v2 · John F. Wu, Steven Boada2018 · 44 citations2019, MNRAS, 484, 4683
Herschel and ALMA Observations of Massive SZE-selected Clusters1712.04540v2 · John F. Wu, Paula Aguirre, Andrew J. Baker et al.2017 · 6 citations2018, ApJ, 853, 195
Galaxy candidates at z ~ 10 in archival data from the Brightest of Reionizing Galaxies (BoRG[z8]) survey1606.05955v1 · S. R. Bernard, D. Carrasco, M. Trenti et al.2016 · 29 citationsarXiv
A new proof of a formula for the type fusion rules1408.4353v1 · Amy Barker, David Swinarski, John Wu et al.2014 · 5 citationsarXiv
Career total: at least 75 works. 46 are in this corpus.
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