Gautham Narayan

According to our database, Gautham Narayan authored at least 10 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration.

LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz, Matthew R. Becker, Biswajit Biswas, Rahul Biswas, Boris Bolliet, Adam S. Bolton, Clecio R. Bom, Raphaël Bonnet-Guerrini, Alexandre Boucaud, Jean-Eric Campagne, Chihway Chang, Aleksandra Ciprijanovic, Johann Cohen-Tanugi, Michael W. Coughlin, John Franklin Crenshaw, Juan C. Cuevas-Tello, Juan de Vicente, Seth W. Digel, Steven Dillmann, Mariano Javier de León Dominguez Romero, Alex Drlica-Wagner, Sydney Erickson, Alexander T. Gagliano, Christos Georgiou, Aritra Ghosh, Matthew Grayling, Kirill A. Grishin, Alan Heavens, Lindsay R. House, Mustapha Ishak, Wassim Kabalan, Arun Kannawadi, François Lanusse, C. Danielle Leonard, Pierre-François Léget, Michelle Lochner, Yao-Yuan Mao, Peter Melchior, Grant Merz, Martin Millon, Anais Möller, Gautham Narayan, Yuuki Omori, Hiranya Peiris, Laurence Perreault Levasseur, Andrés Alejandro Plazas Malagón, Nesar Ramachandra, Benjamin Remy, Cécile Roucelle, Jaime Ruiz-Zapatero, Stefan Schuldt, Ignacio Sevilla-Noarbe, Ved G. Shah, Tjitske Starkenburg, Stephen Thorp, Laura Toribio San Cipriano, Tilman Tröster, Roberto Trotta, Padma Venkatraman, Amanda Wasserman, Tim White, Justine Zeghal, Tianqing Zhang, Yuanyuan Zhang

CoRR, January, 2026

SELDON: Supernova Explosions Learned by Deep ODE Networks.

Jiezhong Wu, Jack O'Brien, Jennifer Li, M. S. Krafczyk, Ved G. Shah, Amanda Wasserman, Daniel W. Apley, Gautham Narayan, Noelle I. Samia

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation.

Andrew Engel, Nell Byler, Adam Tsou, Gautham Narayan, Emmanuel Bonilla, Ian Smith

CoRR, January, 2025

ORACLE: A Real-Time, Hierarchical, Deep-Learning Photometric Classifier for the LSST.

Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, LSST Dark Energy Science Collaboration

CoRR, January, 2025

2024

Preliminary Report on Mantis Shrimp: a Multi-Survey Computer Vision Photometric Redshift Model.

Andrew Engel, Gautham Narayan, Nell Byler

CoRR, 2024

2022

Machine Learning and Cosmology.

Cora Dvorkin, Siddharth Mishra-Sharma, Brian Nord, V. Ashley Villar, Camille Avestruz, Keith Bechtol, Aleksandra Ciprijanovic, Andrew J. Connolly, Lehman H. Garrison, Gautham Narayan, Francisco Villaescusa-Navarro

CoRR, 2022

2021

Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data.

Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

CoRR, 2021

Real-time detection of anomalies in large-scale transient surveys.

Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

CoRR, 2021

2019

RAPID: Early Classification of Explosive Transients using Deep Learning.

Daniel Muthukrishna, Gautham Narayan, Kaisey S. Mandel, Rahul Biswas, Renée Hlozek

CoRR, 2019

A machine learning classifier for microlensing in wide-field surveys.

Daniel Godines, Etienne Bachelet, Gautham Narayan, R. A. Street

Astron. Comput., 2019