Michael S. F. Kirk

According to our database, Michael S. F. Kirk authored at least 12 papers between 2020 and 2024.

Collaborative distances:

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

2024

Neural-Based Compression Scheme for Solar Image Data.

Ali Zafari, Atefeh Khoshkhahtinat, Jeremy A. Grajeda, Piyush M. Mehta, Nasser M. Nasrabadi, Laura E. Boucheron, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

IEEE Trans. Aerosp. Electron. Syst., February, 2024

2023

Science Platforms for Heliophysics Data Analysis.

Monica G. Bobra, Will T. Barnes, Thomas Y. Chen, Mark C. M. Cheung, Laura A. Hayes, Jack Ireland, Miho Janvier, Michael S. F. Kirk, James Mason, Stuart Mumford, Paul J. Wright

CoRR, 2023

Science Applications of the Active Cooling for Multispectral Earth Sensors (ACMES) Mission.

Charles Swenson, Lucas Anderson, Rowan Antonuccio, Chad Fish, Michael Kirk, Benjamin Lewis, Bruno Mattos, Justin Wellington, Miguel Nunes, Robert Wright

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Spectrometer for Methane Monitoring Using a Tilted Interference Filter.

Bruno Mattos, Michael Kirk, Alan Marchant, Charles Swenson, Steve Brezenski, Lucas Anderson, Chad Fish, John Noto, Jason Powell, Nicholas Wallace, Mark Schoeberl

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Multi-Spectral Entropy Constrained Neural Compression of Solar Imagery.

Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

Proceedings of the International Conference on Machine Learning and Applications, 2023

Context-Aware Neural Video Compression on Solar Dynamics Observatory.

Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Michael S. F. Kirk, Daniel Da Silva

Proceedings of the International Conference on Machine Learning and Applications, 2023

2022

Deep Learning for Space Weather Prediction: Bridging the Gap between Heliophysics Data and Theory.

John C. Dorelli, Christopher M. Bard, Thomas Y. Chen, Daniel da Silva, Luiz Fernando Guides dos Santos, Jack Ireland, Michael Kirk, Ryan McGranaghan, Ayris Narock, Teresa Nieves-Chinchilla, Marilia Samara, Menelaos Sarantos, Pete Schuck, Barbara J. Thompson

CoRR, 2022

Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050.

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

CoRR, 2022

Attention-Based Generative Neural Image Compression on Solar Dynamics Observatory.

Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Daniel Da Silva, Michael S. F. Kirk

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

COVID-19 and Beyond: Taming the Virtual Healthcare Tiger with Colored Petri Nets based Modeling and Simulation.

Vijay Gehlot, Elliot B. Sloane, Michael Kirk, Eric Miller, Jonathan L. Schaffer, Nilmini Wickramasinghe

Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

2020

SunPy: A Python package for Solar Physics.

Stuart Mumford, Nabil Freij, Steven Christe, Jack Ireland, Florian Mayer, V. Keith Hughitt, Albert J. Shih, Daniel Ryan, Simon Liedtke, David Pérez-Suárez, Pritish Chakraborty, Vishnunarayan K, Andrew Inglis, Punyaslok Pattnaik, Brigitta M. Sipocz, Rishabh Sharma, Andrew Leonard, David Stansby, Russell J. Hewett, Alex Hamilton, Laura Hayes, Asish Panda, Matt Earnshaw, Nitin Choudhary, Ankit Kumar, Prateek Chanda, Md. Akramul Haque, Michael Kirk, Michael Mueller, Sudarshan Konge, Rajul Srivastava, Yash Jain, Samuel Bennett, Ankit Baruah, Will T. Barnes, Michael Charlton, Shane A. Maloney, Nicky Chorley, Himanshu, Sanskar Modi, James Mason, Jose Rozo, Larry Manley, Agneet Chatterjee, John Evans, Michael Malocha, Monica G. Bobra, Sourav Ghosh, Dominik Stanczak, Ruben De Visscher, Shresth Verma, Ankit Agrawal, Dumindu Buddhika, Swapnil Sharma, Jongyeob Park, Matt Bates, Dhruv Goel, Garrison Taylor, Goran Cetusic, Jacob, Mateo Inchaurrandieta, Sally Dacie, Sanjeev Dubey, Deepankar Sharma, Erik Bray, Jai Rideout, Serge Zahniy, Tomas Meszaros, Abhigyan Bose, André Chicrala, Ankit, Chloé Guennou, Daniel D'avella, Daniel Williams, Jordan Ballew, Nick Murphy, Priyank Lodha, Thomas Robitaille, Yash Krishan, Andrew Hill, Arthur Eigenbrot, Benjamin Mampaey, Bernhard Wiedemann, Carlos Molina, Duygu Keskek, Ishtyaq Habib, Joseph Letts, Juanjo Bazán, Quinn Arbolante, Reid Gomillion, Yash Kothari, Yash Sharma, Abigail Stevens, Adrian M. Price-Whelan, Ambar Mehrotra, Arseniy Kustov, Brandon Stone, Trung Dang, Emmanuel Arias, Fionnlagh Dover, Freek Verstringe, Gulshan Kumar, Harsh Mathur, Igor Babuschkin, Jaylen Wimbish, Juan Buitrago-Casas, Kalpesh Krishna, Kaustubh Hiware, Manas Mangaonkar, Matthew Mendero, Mickaël Schoentgen, Norbert Gyenge, Ole Streicher, Rajasekhar Mekala, Rishabh Mishra, Shashank Srikanth, Sarthak Jain, Tannmay Yadav, Tessa Wilkinson, Tiago Pereira, Yudhik Agrawal, Jamescalixto, Yasintoda, Sophie Murray

J. Open Source Softw., 2020

Identifying Flux Rope Signatures Using a Deep Neural Network.

Luiz F. G. dos Santos, Ayris Narock, Teresa Nieves-Chinchilla, Marlon Núñez, Michael Kirk

CoRR, 2020