Applications of Deep Learning to Physics Workflows
Manan Agarwal,Jay Alameda,Jeroen Audenaert,Will Benoit,Damon Beveridge,Meghna Bhattacharya,Chayan Chatterjee,Deep Chatterjee, Andy Chen, Muhammed Saleem Cholayil, Chia-Jui Chou, Sunil Choudhary,Michael Coughlin,Maximilian Dax, Aman Desai,Andrea Di Luca,Javier Mauricio Duarte,Steven Farrell,Yongbin Feng, Pooyan Goodarzi,Ekaterina Govorkova,Matthew Graham,Jonathan Guiang,Alec Gunny,Weichangfeng Guo,Janina Hakenmueller,Ben Hawks,Shih-Chieh Hsu,Pratik Jawahar,Xiangyang Ju,Erik Katsavounidis,Manolis Kellis,Elham E Khoda, Fatima Zahra Lahbabi, Van Tha Bik Lian,Mia Liu,Konstantin Malanchev,Ethan Marx,William Patrick McCormack,Alistair McLeod,Geoffrey Mo,Eric Anton Moreno,Daniel Muthukrishna,Gautham Narayan, Andrew Naylor,Mark Neubauer,Michael Norman,Rafia Omer,Kevin Pedro,Joshua Peterson,Michael Pürrer,Ryan Raikman, Shivam Raj,George Ricker, Jared Robbins,Batool Safarzadeh Samani,Kate Scholberg,Alex Schuy,Vasileios Skliris,Siddharth Soni,Niharika Sravan,Patrick Sutton,Victoria Ashley Villar, Xiwei Wang,Linqing Wen,Frank Wuerthwein,Tingjun Yang, Shu-Wei Yeh arXiv (Cornell University)（2023）
Key words
Scientific Workflows,Task Scheduling,Workflow Management,Scientific Computing
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