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Journal Articles
- 2021
[j2]Wei Lu
, Carlos Bueno, Nicholas P. Schafer, Joshua Moller, Shikai Jin, Xun Chen, Mingchen Chen, Xinyu Gu, Aram Davtyan, Juan J. de Pablo, Peter G. Wolynes:
OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations. PLoS Comput. Biol. 17(2) (2021)- 2020
- [j1]Ganesh Sivaraman, Nicholas E. Jackson, Benjamín Sánchez-Lengeling, Álvaro Vázquez-Mayagoitia, Alán Aspuru-Guzik, Venkatram Vishwanath, Juan J. de Pablo:
A machine learning workflow for molecular analysis: application to melting points. Mach. Learn. Sci. Technol. 1(2): 25015 (2020)
Conference and Workshop Papers
- 2019
- [c4]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 - [c3]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 - 2017
- [c2]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 - 2016
- [c1]Roselyne Tchoua, Kyle Chard, Debra Audus, Jian Qin, Juan de Pablo, Ian T. Foster:
A Hybrid Human-computer Approach to the Extraction of Scientific Facts from the Literature. ICCS 2016: 386-397
Informal and Other Publications
- 2023
- [i1]Hyun Park, Boyuan Yu, Juhae Park, Ge Sun, Emad Tajkhorshid, Juan J. de Pablo, Ludwig Schneider:
Prediction of Diblock Copolymer Morphology via Machine Learning. CoRR abs/2308.16886 (2023)
Coauthor Index
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