DM
D. Muthukrishna
astro-ph.IMastro-ph.HEcs.LGastro-ph.COastro-ph.SRastro-ph.EPastro-ph.GAgr-qcstat.MLcs.AI
On Valency
published · living versionsW_tq2xehnt·v1 · currentpublished
The Young Supernova Experiment: Survey Goals, Overview, and Operations
with D. O. Jones, R. J. Foley, G. Narayan, J. Hjorth +66
1 version
W_cx87qxgm·v1published
W_r3rdn45f·v1published
Preprints & journals
38 papers in the corpus · 2016–2026TS23/McDonald and FIES/NOT strike again. Two new warm Jupiter systems and outer companions in a third2609.30915v1 · E. Knudstrup, D. Gandolfi, W. D. Cochran et al.2026 · 0 citationsarXiv
Deep 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
The GAPS Programme at TNG. LXXIII. Confirmation of the hot sub-Neptune TOI-4602 b (HD 25295 b), a key target for future atmospheric characterization2604.11728v1 · C. Di Maio, S. Benatti, D. Locci et al.2026 · 0 citationsarXiv
Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics2604.09787v2 · Pablo Mercader-Perez, Carolina Cuesta-Lazaro, Daniel Muthukrishna et al.2026 · 0 citationsarXiv
ASTRAFier: A Novel and Scalable Transformer-based Stellar Variability Classifier2604.07437v1 · Paul F. X. Gregory, Jeroen Audenaert, Mykyta Kliapets et al.2026 · 0 citationsarXiv
QLP Data Release Notes 004: TESS-Gaia Light Curve Photometry Implementation2603.22236v1 · Glen Petitpas, Jack Haviland, Te Han et al.2026 · 2 citationsarXiv
Simulation-Based Pretraining and Domain Adaptation for Astronomical Time Series with Minimal Labeled Data2510.12958v1 · Rithwik Gupta, Daniel Muthukrishna, Jeroen Audenaert2025 · 0 citationsarXiv
ABC-SN: Attention Based Classifier for Supernova Spectra2507.22106v3 · Willow Fox Fortino, Federica B. Bianco, Pavlos Protopapas et al.2025 · 3 citationsApJ 1000 14 (2026)
Causal Foundation Models: Disentangling Physics from Instrument Properties2507.05333v1 · Jeroen Audenaert, Daniel Muthukrishna, Paul F. Gregory et al.2025 · 0 citationsarXiv
Transfer Learning for Transient Classification: From Simulations to Real Data and ZTF to LSST2502.18558v2 · Rithwik Gupta, Daniel Muthukrishna, Nabeel Rehemtulla et al.2025 · 6 citationsarXiv
A Disintegrating Rocky Planet with Prominent Comet-like Tails Around a Bright Star2501.05431v3 · Marc Hon, Saul Rappaport, Avi Shporer et al.2025 · 10 citationsarXiv
A Classifier-Based Approach to Multi-Class Anomaly Detection Applied to Astronomical Time-Series2408.08888v1 · Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner2024 · 1 citationarXiv
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients2403.14742v2 · Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner2024 · 9 citationsarXiv
Predicting the Age of Astronomical Transients from Real-Time Multivariate Time Series2311.17143v1 · Hali Huang, Daniel Muthukrishna, Prajna Nair et al.2023 · 0 citationsarXiv
Four years of Type Ia Supernovae Observed by TESS: Early Time Light Curve Shapes and Constraints on Companion Interaction Models2307.11815v2 · M. M. Fausnaugh, P. J. Vallely, M. A. Tucker et al.2023 · 31 citationsarXiv
Applications of Deep Learning to physics workflows2306.08106v1 · Manan Agarwal, Jay Alameda, Jeroen Audenaert et al.2023 · 1 citationarXiv
Identifying Exoplanets with Deep Learning. V. Improved Light Curve Classification for TESS Full Frame Image Observations2301.01371v1 · Evan Tey, Dan Moldovan, Michelle Kunimoto et al.2023 · 23 citationsarXiv
Enabling the discovery of fast transients: A kilonova science module for the Fink broker2210.17433v2 · B. Biswas, E. E. O. Ishida, J. Peloton et al.2022 · 16 citationsA&A 677, A77 (2023)
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
Real-Time Detection of Anomalies in Large-Scale Transient Surveys2111.00036v2 · Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner et al.2021 · 25 citationsarXiv
El-CID: A filter for Gravitational-wave Electromagnetic Counterpart Identification2108.04166v3 · Deep Chatterjee, Gautham Narayan, Patrick D. Aleo et al.2021 · 11 citationsarXiv
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
The Young Supernova Experiment: Survey Goals, Overview, and Operations2010.09724v2 · D. O. Jones, R. J. Foley, G. Narayan et al.2020 · 112 citationsarXivon Valency
Unsupervised machine learning for transient discovery in Deeper, Wider, Faster light curves2008.04666v1 · Sara Webb, Michelle Lochner, Daniel Muthukrishna et al.2020 · 37 citationsarXiv
Using machine learning for transient classification in searches for gravitational-wave counterparts1912.06383v2 · Cosmin Stachie, Michael W. Coughlin, Nelson Christensen et al.2019 · 18 citationsarXiv
RAPID: Early Classification of Explosive Transients using Deep Learning1904.00014v2 · Daniel Muthukrishna, Gautham Narayan, Kaisey S. Mandel et al.2019 · 148 citationsPASP 131, 118002 (2019)on Valency
Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)1903.11756v2 · R. Kessler, G. Narayan, A. Avelino et al.2019 · 144 citationsarXivon Valency
4MOST: Project overview and information for the First Call for Proposals1903.02464v2 · R.S. de Jong, O. Agertz, A. Agudo Berbel et al.2019 · 406 citationsThe Messenger, 2019, 175, 3
DASH: Deep Learning for the Automated Spectral Classification of Supernovae and their Hosts1903.02557v3 · Daniel Muthukrishna, David Parkinson, Brad Tucker2019 · 54 citationsApJ 885, 85 (2019)
First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Survey Overview and Supernova Spectroscopy1811.09565v1 · C. B. D'Andrea, M. Smith, M. Sullivan et al.2018 · 51 citationsarXiv
First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters1811.02374v4 · T. M. C. Abbott, S. Allam, P. Andersen et al.2018 · 273 citationshttps://ui.adsabs.harvard.edu/abs/2019ApJ...872L..30A
First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation1811.02377v5 · D. Brout, D. Scolnic, R. Kessler et al.2018 · 133 citationsThe Astrophysical Journal, Volume 874, Issue 2, article id. 150, 29 pp. (2019)
First Cosmology Results using Type Ia Supernova from the Dark Energy Survey: Simulations to Correct Supernova Distance Biases1811.02379v4 · R. Kessler, D. Brout, C. B. D'Andrea et al.2018 · 90 citationshttps://ui.adsabs.harvard.edu/abs/2019MNRAS.485.1171K
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
Multi-Messenger Astrophysics: Harnessing the Data Revolution1807.04780v1 · Gabrielle Allen, Warren Anderson, Erik Blaufuss et al.2018 · 7 citationsarXiv
OzDES multifibre spectroscopy for the Dark Energy Survey: Three year results and first data release1708.04526v1 · M. J. Childress, C. Lidman, T. M. Davis et al.2017 · 94 citationsarXiv
A cosmographic analysis of the transition to acceleration using SN-Ia and BAO1607.01884v2 · Daniel Muthukrishna, David Parkinson2016 · 26 citationsJournal of Cosmology and Astroparticle Physics, Issue 11, article id. 052, (2016)
Career total: 93 works. 38 are in this corpus.
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