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2020 – today
- 2023
[i5]Yasir Alanazi, Malachi Schram, Kishansingh Rajput, Steven Goldenberg, Lasitha Vidyaratne, Chris Pappas, Majdi I. Radaideh, Dan Lu, Pradeep Ramuhalli, Sarah Cousineau:
Multi-module based CVAE to predict HVCM faults in the SNS accelerator. CoRR abs/2304.10639 (2023)- 2022
- [j3]Majdi I. Radaideh
, Chris Pappas, Jared Walden, Dan Lu, Lasitha Vidyaratne, Thomas Britton, Kishansingh Rajput, Malachi Schram, Sarah Cousineau:
Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders. Digit. Signal Process. 130: 103704 (2022) - 2021
- [j2]Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishniah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j1]Jan Strube, Malachi Schram, Sabiha Rustam, Zachary Kennedy, Tamás Varga:
Identifying build orientation of 3D-printed materials using convolutional neural networks. Stat. Anal. Data Min. 14(6): 575-582 (2021) - [i4]D. Kafkes, Malachi Schram:
Developing Robust Digital Twins and Reinforcement Learning for Accelerator Control Systems at the Fermilab Booster. CoRR abs/2105.12847 (2021) - [i3]Willem Blokland, Pradeep Ramuhalli, Charles Peters, Yigit Yucesan, Alexander Zhukov, Malachi Schram, Kishansingh Rajput, Torri Jeske:
Uncertainty aware anomaly detection to predict errant beam pulses in the SNS accelerator. CoRR abs/2110.12006 (2021) - [i2]Amber Boehnlein, Markus Diefenthaler, Cristiano Fanelli, Morten Hjorth-Jensen, Tanja Horn, Michelle P. Kuchera, Dean Lee, Witold Nazarewicz, Kostas Orginos, Peter Ostroumov, Long-Gang Pang, Alan Poon, Nobuo Sato, Malachi Schram, Alexander Scheinker, Michael S. Smith, Xin-Nian Wang, Veronique Ziegler:
Artificial Intelligence and Machine Learning in Nuclear Physics. CoRR abs/2112.02309 (2021)
2010 – 2019
- 2019
- [c7]Joshua Suetterlein, Ryan D. Friese, Nathan R. Tallent, Malachi Schram:
TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows. IEEE BigData 2019: 383-394 - 2018
- [c6]Alok Singh, Ilkay Altintas, Malachi Schram, Nathan R. Tallent:
Deep Learning for Enhancing Fault Tolerant Capabilities of Scientific Workflows. IEEE BigData 2018: 3905-3914 - [c5]Ryan D. Friese, Nathan R. Tallent, Malachi Schram, Mahantesh Halappanavar, Kevin J. Barker:
Optimizing Distributed Data-Intensive Workflows. CLUSTER 2018: 279-289 - [i1]Alok Singh, Eric G. Stephan, Malachi Schram, Ilkay Altintas:
Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows. CoRR abs/1804.06062 (2018) - 2017
- [c4]Alok Singh, Eric G. Stephan, Malachi Schram, Ilkay Altintas:
Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows. eScience 2017: 586-591 - [c3]Ryan D. Friese, Mahantesh Halappanavar, Arun V. Sathanur, Malachi Schram, Darren J. Kerbyson, Luis de la Torre:
Towards Efficient Resource Allocation for Distributed Workflows Under Demand Uncertainties. JSSPP 2017: 103-121 - 2016
- [c2]Alok Singh, Eric G. Stephan, Todd Elsethagen, Matt MacDuff, Bibi Raju, Malachi Schram, Kerstin Kleese van Dam, Darren J. Kerbyson, Ilkay Altintas:
Leveraging large sensor streams for robust cloud control. IEEE BigData 2016: 2115-2120 - 2015
- [c1]Mahantesh Halappanavar, Malachi Schram, Luis de la Torre, Kevin J. Barker, Nathan R. Tallent, Darren J. Kerbyson:
Towards efficient scheduling of data intensive high energy physics workflows. WORKS@SC 2015: 3:1-3:9
Coauthor Index
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last updated on 2023-05-03 23:36 CEST by the dblp team
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