
Logan T. Ward
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2020 – today
- 2021
- [j1]Zhuozhao Li, Ryan Chard, Logan T. Ward, Kyle Chard, Tyler J. Skluzacek, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster:
DLHub: Simplifying publication, discovery, and use of machine learning models in science. J. Parallel Distributed Comput. 147: 64-76 (2021) - [i5]Zhi Hong, J. Gregory Pauloski, Logan T. Ward, Kyle Chard, Ben Blaiszik, Ian T. Foster:
AI- and HPC-enabled Lead Generation for SARS-CoV-2: Models and Processes to Extract Druglike Molecules Contained in Natural Language Text. CoRR abs/2101.04617 (2021) - [i4]Logan T. Ward, Jenna A. Bilbrey, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman:
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19. CoRR abs/2102.04977 (2021) - 2020
- [i3]Sutanay Choudhury, Jenna A. Bilbrey, Logan T. Ward, Sotiris S. Xantheas, Ian T. Foster, Joseph P. Heindel, Ben Blaiszik, Marcus E. Schwarting:
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data. CoRR abs/2012.00131 (2020)
2010 – 2019
- 2019
- [c8]Roselyne Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Debra Audus, Shrayesh Patel, Juan de Pablo, Ian T. Foster:
Active Learning Yields Better Training Data for Scientific Named Entity Recognition. eScience 2019: 126-135 - [c7]Roselyne B. Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Alexander Belikov, Debra J. Audus, Shrayesh Patel, Juan J. de Pablo, Ian T. Foster:
Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort. ICCS (1) 2019: 398-411 - [c6]Ryan Chard, Zhuozhao Li, Kyle Chard, Logan T. Ward, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster:
DLHub: Model and Data Serving for Science. IPDPS 2019: 283-292 - [c5]Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal:
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. KDD 2019: 2385-2393 - [c4]Tyler J. Skluzacek, Ryan Chard, Ryan Wong, Zhuozhao Li, Yadu N. Babuji, Logan T. Ward, Ben Blaiszik, Kyle Chard, Ian T. Foster:
Serverless Workflows for Indexing Large Scientific Data. WOSC@Middleware 2019: 43-48 - [c3]Ryan Chard, Logan T. Ward, Zhuozhao Li, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Kyle Chard, Ben Blaiszik, Ian T. Foster:
Publishing and Serving Machine Learning Models with DLHub. PEARC 2019: 73:1-73:7 - [i2]Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal:
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. CoRR abs/1907.03222 (2019) - 2018
- [c2]Matt Baughman, Ryan Chard, Logan T. Ward, Jason Pitt, Kyle Chard, Ian T. Foster:
Profiling and Predicting Application Performance on the Cloud. UCC 2018: 21-30 - [i1]Ryan Chard, Zhuozhao Li, Kyle Chard, Logan T. Ward, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster:
DLHub: Model and Data Serving for Science. CoRR abs/1811.11213 (2018) - 2017
- [c1]Roselyne B. Tchoua, Kyle Chard, Debra J. Audus, Logan T. Ward, Joshua Lequieu, Juan J. de Pablo, Ian T. Foster:
Towards a Hybrid Human-Computer Scientific Information Extraction Pipeline. eScience 2017: 109-118
Coauthor Index

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