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ORCIDRyan M. McGranaghan
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2020 – today
- 2025
[i7]Sujit Roy, Johannes Schmude, Rohit Lal, Vishal Gaur, Marcus Freitag, Julian Kuehnert, Theodore van Kessel, Dinesha Hegde, Andrés Muñoz-Jaramillo, Johannes Jakubik, Etienne Eben Vos, Kshitiz Mandal, Ata Akbari Asanjan, João Lucas de Sousa Almeida, Amy Lin, Talwinder Singh, Yanghui Kang, Chetraj Pandey, Jinsu Hong, Berkay Aydin, Thorsten Kurth, Ryan M. McGranaghan
, Spiridon Kasapis, Vishal Upendran, Shah Bahauddin, Daniel da Silva, Nikolai V. Pogorelov, Anne Spalding, Campbell D. Watson, Manil Maskey, Madhulika Guhathakurta, Juan Bernabé-Moreno, Rahul Ramachandran:
Surya: Foundation Model for Heliophysics. CoRR abs/2508.14112 (2025)- 2022
- [i6]Vishal Upendran, Panagiotis Tigas, Banafsheh Ferdousi, Téo Bloch, Mark C. M. Cheung, Siddha Ganju, Asti Bhatt, Ryan M. McGranaghan, Yarin Gal:
Global geomagnetic perturbation forecasting using Deep Learning. CoRR abs/2205.12734 (2022) - [i5]Ryan M. McGranaghan, Barbara J. Thompson, Enrico Camporeale, J. Bortnik, Monica G. Bobra, G. Lapenta, S. Wing, Bala Poduval, S. Lotz, S. Murray, Michael S. F. Kirk, T. Y. Chen, H. M. Bain, P. Riley, B. Tremblay, M. Cheung, Véronique Delouille:
Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050. CoRR abs/2212.13325 (2022) - 2021
- [c3]Jack Ziegler, Ryan M. McGranaghan:
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes. ICMLA 2021: 1189-1196 - [c2]Toryn L. J. Schafer, Ryan M. McGranaghan, Mila Getmansky Sherman, Mei-Ling E. Feng, Olukunle O. Owolabi, Sean E. Ryan, Marie-Christine Düker, Michael Jauch, David S. Matteson:
Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research. KDD 2021: 4155-4156 - [c1]Cogan Shimizu, Ryan M. McGranaghan, Aaron Eberhart, Adam C. Kellerman:
Towards a Modular Ontology for Space Weather Research. WOP (Book) 2021: 299-311 - [i4]Panagiotis Tigas, Téo Bloch, Vishal Upendran, Banafsheh Ferdoushi, Mark C. M. Cheung, Siddha Ganju, Ryan M. McGranaghan, Yarin Gal, Asti Bhatt:
Global Earth Magnetic Field Modeling and Forecasting with Spherical Harmonics Decomposition. CoRR abs/2102.01447 (2021) - [i3]Jack Ziegler, Ryan M. McGranaghan:
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes. CoRR abs/2111.14998 (2021) - 2020
- [i2]Gelu Nita, Manolis K. Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason T. L. Wang, Rafal A. Angryk, Berkay Aydin, Azim Ahmadzadeh, Xiaoli Bai, Timothy Bastian, Soukaina Filali Boubrahimi, Bin Chen, Alisdair Davey, Sheldon Fereira, Gregory Fleishman, Dale Gary, Andrew Gerrard, Gregory Hellbourg, Katherine G. Herbert, Jack Ireland, Egor Illarionov, Natsuha Kuroda, Qin Li, Chang Liu, Yuexin Liu, Hyomin Kim, Dustin Kempton, Ruizhe Ma, Petrus C. Martens, Ryan M. McGranaghan, Edward Semones, John T. Stefan, Andrey Stejko, Yaireska Collado-Vega, Meiqi Wang, Yan Xu, Sijie Yu:
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations. CoRR abs/2006.12224 (2020) - [i1]Cogan Shimizu, Ryan M. McGranaghan, Aaron Eberhart, Adam C. Kellerman:
Towards a Modular Ontology for Space Weather Research. CoRR abs/2009.12285 (2020)
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