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Picture for Ashish Mahabal

Ashish Mahabal

California Institute of Technology, USA

Tails: Chasing Comets with the Zwicky Transient Facility and Deep Learning


Feb 26, 2021
Dmitry A. Duev, Bryce T. Bolin, Matthew J. Graham, Michael S. P. Kelley, Ashish Mahabal, Eric C. Bellm, Michael W. Coughlin, Richard Dekany, George Helou, Shrinivas R. Kulkarni, Frank J. Masci, Thomas A. Prince, Reed Riddle, Maayane T. Soumagnac, Stéfan J. van der Walt


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Nigraha: Machine-learning based pipeline to identify and evaluate planet candidates from TESS


Feb 22, 2021
Sriram Rao, Ashish Mahabal, Niyanth Rao, Cauligi Raghavendra

* journal = {Monthly Notices of the Royal Astronomical Society}, volume = {502}, number = {2}, pages = {2845-2858}, year = {2021}, month = {01}, issn = {0035-8711}, 
* 15 pages, 18 figures, and 6 tables. Accepted for publication as a full paper in Monthly Notices of the Royal Astronomical Society 

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Enabling real-time multi-messenger astrophysics discoveries with deep learning


Nov 26, 2019
E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

* Nature Reviews Physics volume 1, pages 600-608 (2019) 
* Invited Expert Recommendation for Nature Reviews Physics. The art work produced by E. A. Huerta and Shawn Rosofsky for this article was used by Carl Conway to design the cover of the October 2019 issue of Nature Reviews Physics 

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Eliminating artefacts in Polarimetric Images using Deep Learning


Nov 19, 2019
Dhruv Paranjpye, Ashish Mahabal, A. N. Ramaprakash, Gina Panopoulou, Kieran Cleary, Anthony Readhead, Dmitry Blinov, Kostas Tassis

* 7 pages, 15 figures 

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New methods to assess and improve LIGO detector duty cycle


Oct 26, 2019
Ayon Biswas, Jess McIver, Ashish Mahabal


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Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era


Feb 01, 2019
Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

* 15 pages, no figures. White paper based on the "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at NCSA, October 17-19, 2018 http://www.ncsa.illinois.edu/Conferences/DeepLearningLSST/ 

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Effective Image Differencing with ConvNets for Real-time Transient Hunting


Oct 04, 2017
Nima Sedaghat, Ashish Mahabal


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Deep-Learnt Classification of Light Curves


Sep 19, 2017
Ashish Mahabal, Kshiteej Sheth, Fabian Gieseke, Akshay Pai, S. George Djorgovski, Andrew Drake, Matthew Graham, the CSS/CRTS/PTF Collaboration

* 2017 IEEE Symposium Series on Computational Intelligence (SSCI), Honolulu, HI, USA, 2017, p2757 
* 8 pages, 9 figures, 6 tables, 2 listings. Accepted to 2017 IEEE Symposium Series on Computational Intelligence (SSCI) 

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Bigger Buffer k-d Trees on Multi-Many-Core Systems


Dec 09, 2015
Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes


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