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Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers


Mar 04, 2021
Agastya P. Bhati , Shunzhou Wan , Dario Alfè , Austin R. Clyde , Mathis Bode , Li Tan , Mikhail Titov , Andre Merzky , Matteo Turilli , Shantenu Jha , Roger R. Highfield , Walter Rocchia , Nicola Scafuri , Sauro Succi , Dieter Kranzlmüller , Gerald Mathias , David Wifling , Yann Donon , Alberto Di Meglio , Sofia Vallecorsa , Heng Ma , Anda Trifan , Arvind Ramanathan , Tom Brettin , Alexander Partin , Fangfang Xia , Xiaotan Duan , Rick Stevens , Peter V. Coveney


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Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release


May 28, 2020
Yadu Babuji , Ben Blaiszik , Tom Brettin , Kyle Chard , Ryan Chard , Austin Clyde , Ian Foster , Zhi Hong , Shantenu Jha , Zhuozhao Li , Xuefeng Liu , Arvind Ramanathan , Yi Ren , Nicholaus Saint , Marcus Schwarting , Rick Stevens , Hubertus van Dam , Rick Wagner

* 11 pages, 5 figures 

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A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning


May 04, 2020
Austin Clyde , Tom Brettin , Alexander Partin , Maulik Shaulik , Hyunseung Yoo , Yvonne Evrard , Yitan Zhu , Fangfang Xia , Rick Stevens


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Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research


Sep 01, 2019
Prasanna Balaprakash , Romain Egele , Misha Salim , Stefan Wild , Venkatram Vishwanath , Fangfang Xia , Tom Brettin , Rick Stevens

* SC '19: IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis, November 17--22, 2019, Denver, CO 

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