ML
Michelle Lochner
astro-ph.IMastro-ph.COastro-ph.GAastro-ph.HEcs.LGastro-ph.SRstat.MLcs.AIcs.CVastro-ph.EP
On Valency
published · living versionsW_qpybb2aj·v1 · currentpublished
Science-Driven Optimization of the LSST Observing Strategy
with LSST Science Collaboration, Phil Marshall, Timo Anguita, Federica B. Bianco +100
1 version
Preprints & journals
55 papers in the corpus · 2013–2026Enabling New Discoveries with Machine Learning2609.10109v1 · Michelle Lochner2026 · 0 citationsM. Lochner, "Enabling New Discoveries with Machine Learning," Proceedings of the International Astronomical Union, vol. 20, no. A32, pp. 287-293, 2024
The promise of self-supervised and active learning for Strong Lens discovery: Astronomaly applied to KiDS2609.00154v2 · Margherita Grespan, Aprajita Verma, Michelle Lochner et al.2026 · 0 citationsarXiv
A targeted machine learning approach for detecting diffuse radio emission with Astronomaly: Protege2602.15930v2 · Verlon Etsebeth, Michelle Lochner, Konstantinos Kolokythas et al.2026 · 0 citationsarXiv
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration2601.14235v1 · Eric Aubourg, Camille Avestruz, Matthew R. Becker et al.2026 · 0 citationsarXiv
Uniform Rolling: An LSST Observing Cadence Offering Sufficient Survey Uniformity for Comprehensive Cosmological Analysis2512.16478v1 · Boris Leistedt, Matthew R. Becker, Humna Awan et al.2025 · 1 citationarXiv
A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host Galaxy Redshifts and Supernova Classification2512.06319v2 · Ayan Mitra, Richard Kessler, Rebecca C. Chen et al.2025 · 1 citationarXiv
Discovering Cataclysmic Variables from the Rubin Observatory LSST2509.07298v1 · D.A.H. Buckley, Y. Tampo, P. Szkody et al.2025 · 0 citationsarXiv
Astronomaly Protege: Discovery Through Human-Machine Collaboration2411.04188v3 · Michelle Lochner, Lawrence Rudnick2024 · 9 citations2025 AJ 169 121
Finding radio transients with anomaly detection and active learning based on volunteer classifications2410.01034v2 · Alex Andersson, Chris Lintott, Rob Fender et al.2024 · 6 citationsMNRAS, 2025, 538, 3, pp.1397-1414
A Classifier-Based Approach to Multi-Class Anomaly Detection Applied to Astronomical Time-Series2408.08888v1 · Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner2024 · 1 citationarXiv
TEGLIE: Transformer encoders as strong gravitational lens finders in KiDS2405.11992v1 · Margherita Grespan, Hareesh Thuruthipilly, Agnieszka Pollo et al.2024 · 11 citationsA&A 688, A34 (2024)
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients2403.14742v2 · Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner2024 · 9 citationsarXiv
Enabling Unsupervised Discovery in Astronomical Images through Self-Supervised Representations2311.14157v2 · Koketso Mohale, Michelle Lochner2023 · 18 citationsMNRAS Volume 530, Issue 1, May 2024, Pages 1274--1295
Astronomaly at scale: searching for anomalies amongst 4 million galaxies2309.08660v2 · Verlon Etsebeth, Michelle Lochner, Mike Walmsley et al.2023 · 20 citationsMNRAS Volume 529, Issue 1, March 2024, Pages 732--747
Euclid Preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events2307.08736v2 · L. Leuzzi, M. Meneghetti, G. Angora et al.2023 · 0 citationsAstronomy & Astrophysics,2024, 681, A68
A unique, ring-like radio source with quadrilateral structure detected with machine learning2211.02062v2 · Michelle Lochner, Lawrence Rudnick, Ian Heywood et al.2022 · 31 citationsMNRAS Volume 520, Issue 1, January 2023, Pages 1439-1446
Impact of Rubin Observatory cadence choices on supernovae photometric classification2210.15690v2 · Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner et al.2022 · 9 citationsarXiv
Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae2205.07651v1 · Philippe Gris, Nicolas Regnault, Humna Awan et al.2022 · 19 citationsarXiv
LADUMA: Discovery of a luminous OH megamaser at 2204.02523v1 · Marcin Glowacki, Jordan D. Collier, Amir Kazemi-Moridani et al.2022 · 12 citationsarXiv
Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential2204.01992v1 · Jonathan A. Blazek, Doug Clowe, Thomas E. Collett et al.2022 · 2 citationsarXiv
A Hitchhiker's Guide to Anomaly Detection with Astronomaly2201.10189v1 · Michelle Lochner, Bruce A. Bassett2022 · 0 citationsarXiv
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data2112.08415v1 · Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner et al.2021 · 0 citationsarXiv
The MeerKAT Galaxy Cluster Legacy Survey I. Survey Overview and Highlights2111.05673v1 · K. Knowles, W. D. Cotton, L. Rudnick et al.2021 · 132 citationsarXiv
Real-Time Detection of Anomalies in Large-Scale Transient Surveys2111.00036v2 · Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner et al.2021 · 25 citationsarXiv
Practical Galaxy Morphology Tools from Deep Supervised Representation Learning2110.12735v2 · Mike Walmsley, Anna M. M. Scaife, Chris Lintott et al.2021 · 64 citationsMNRAS Volume 513, Issue 2, June 2022, Pages 1581-1599
Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: a pioneering process of community-focused experimental design2108.01683v2 · Federica B. Bianco, Zeljko Ivezi'c, R. Lynne Jones et al.2021 · 148 citationsarXiv
Considerations for optimizing photometric classification of supernovae from the Rubin Observatory2107.07531v2 · Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner et al.2021 · 17 citations2022 ApJS 258 23
The Deeper, Wider, Faster Program: Exploring stellar flare activity with deep, fast cadenced DECam imaging via machine learning2106.13026v1 · Sara Webb, Chris Flynn, Jeff Cooke et al.2021 · 16 citationsarXiv
Multi-tasking the growth of cosmological structures2105.01613v2 · Louis Perenon, Matteo Martinelli, St'ephane Ili'c et al.2021 · 23 citationsPhys.Dark Univ. 34 (2021) 100898
The Impact of Observing Strategy on Cosmological Constraints with LSST2104.05676v1 · Michelle Lochner, Dan Scolnic, Husni Almoubayyed et al.2021 · 39 citationsApJS 259 58, 2022
Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)2012.12392v1 · R. Hlozek, K. A. Ponder, A. I. Malz et al.2020 · 35 citationsarXiv
Astronomaly: Personalised Active Anomaly Detection in Astronomical Data2010.11202v2 · Michelle Lochner, Bruce A. Bassett2020 · 84 citationsAstronomy and Computing, Volume 36, July 2021, 100481
Unsupervised machine learning for transient discovery in Deeper, Wider, Faster light curves2008.04666v1 · Sara Webb, Michelle Lochner, Daniel Muthukrishna et al.2020 · 37 citationsarXiv
Mini-survey of the northern sky to Dec <+301904.10438v1 · P. Capak, D. Sconlic, J-C. Cuillandre et al.2019 · 1 citationarXiv
Enhancing LSST Science with Euclid Synergy1904.10439v1 · P. Capak, J-C. Cuillandre, F. Bernardeau et al.2019 · 11 citationsarXiv
Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST1903.09323v1 · Rachel Mandelbaum, Jonathan Blazek, Nora Elisa Chisari et al.2019 · 5 citationsarXiv
Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST1903.09325v1 · Jeffrey A. Newman, Jonathan Blazek, Nora Elisa Chisari et al.2019 · 4 citationsarXiv
The Role of Machine Learning in the Next Decade of Cosmology1902.10159v2 · Michelle Ntampaka, Camille Avestruz, Steven Boada et al.2019 · 40 citationsarXiv
Bayesian Anomaly Detection and Classification1902.08627v1 · Ethan Roberts, Bruce A. Bassett, Michelle Lochner2019 · 12 citationsarXiv
Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey1812.00515v2 · Michelle Lochner, Daniel M. Scolnic, Humna Awan et al.2018 · 22 citationsarXiv
Classification of Multiwavelength Transients with Machine Learning1811.08446v2 · K. Sooknunan, M. Lochner, Bruce A. Bassett et al.2018 · 16 citationsMonthly Notices of the Royal Astronomical Society, Volume 502, Issue 1, March 2021, Pages 206-224
The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Selection of a performance metric for classification probabilities balancing diverse science goals1809.11145v2 · A.I. Malz, R. Hlozek, T. Allam Jr et al.2018 · 25 citationsAJ 158 5 171 (2019)
The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set1810.00001v1 · The PLAsTiCC team, Tarek Allam Jr., Anita Bahmanyar et al.2018 · 41 citationsarXiv
DeepSource: Point Source Detection using Deep Learning1807.02701v1 · A. Vafaei Sadr, Etienne. E. Vos, Bruce A. Bassett et al.2018 · 51 citationsMNRAS, Volume 484, Issue 2, April 2019, Pages 2793-2806
Radio Galaxy Shape Measurement with Hamiltonian Monte Carlo in the Visibility Domain1805.06799v3 · M. Rivi, M. Lochner, S.T. Balan et al.2018 · 9 citationsMNRAS 2019, 482(1): 1096-1109
Machine learning cosmological structure formation1802.04271v2 · Luisa Lucie-Smith, Hiranya V. Peiris, Andrew Pontzen et al.2018 · 64 citationsarXiv
Machine Learning-based Brokers for Real-time Classification of the LSST Alert Stream1801.07323v1 · Gautham Narayan, Tayeb Zaidi, Monika D. Soraisam et al.2018 · 108 citationsarXiv
MeerKLASS: MeerKAT Large Area Synoptic Survey1709.06099v1 · Mario G. Santos, Michelle Cluver, Matt Hilton et al.2017 · 62 citationsarXiv
Science-Driven Optimization of the LSST Observing Strategy1708.04058v1 · LSST Science Collaborations: Phil Marshall, Timo Anguita, Federica B. Bianco et al.2017 · 115 citationsarXivon Valency
Redshifts for galaxies in radio continuum surveys from Bayesian model fitting of HI 21-cm lines1704.08278v1 · Ian Harrison, Michelle Lochner, Michael L. Brown2017 · 4 citationsarXiv
Career total: at least 97 works. 55 are in this corpus.Showing the 50 most recent.
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