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2020 – today
- 2020
[i6]Pedro M. Milani, Julia Ling, John K. Eaton:
Turbulent scalar flux in inclined jets in crossflow: counter gradient transport and deep learning modelling. CoRR abs/2001.04600 (2020)
2010 – 2019
- 2019
- [j2]Aditya Konduri
, Hemanth Kolla, W. Philip Kegelmeyer, Timothy M. Shead, Julia Ling, Warren L. Davis IV:
Anomaly detection in scientific data using joint statistical moments. J. Comput. Phys. 387: 522-538 (2019) - [i5]Pedro M. Milani, Julia Ling, John K. Eaton:
Generalization of machine-learned turbulent heat flux models applied to film cooling flows. CoRR abs/1910.03097 (2019) - [i4]Zachary del Rosario, Yoolhee Kim, Matthias Rupp, Erin Antono, Julia Ling:
Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization. CoRR abs/1911.03224 (2019) - [i3]Yoolhee Kim, Edward Kim, Erin Antono, Bryce Meredig, Julia Ling:
Machine-learned metrics for predicting the likelihood of success in materials discovery. CoRR abs/1911.11201 (2019) - 2017
- [c2]Julia Ling, W. Philip Kegelmeyer, Aditya Konduri, Hemanth Kolla, Kevin A. Reed, Timothy M. Shead, Warren L. Davis IV:
Using feature importance metrics to detect events of interest in scientific computing applications. LDAV 2017: 55-63 - [i2]Julia Ling, Maxwell Hutchinson, Erin Antono, Brian DeCost, Elizabeth A. Holm, Bryce Meredig:
Building Data-driven Models with Microstructural Images: Generalization and Interpretability. CoRR abs/1711.00404 (2017) - [i1]Maxwell L. Hutchinson, Erin Antono, Brenna M. Gibbons, Sean Paradiso, Julia Ling, Bryce Meredig:
Overcoming data scarcity with transfer learning. CoRR abs/1711.05099 (2017) - 2016
- [j1]Julia Ling, Reese E. Jones, Jeremy A. Templeton:
Machine learning strategies for systems with invariance properties. J. Comput. Phys. 318: 22-35 (2016) - 2015
- [c1]Julia Ling:
Using Machine Learning to Understand and Mitigate Model Form Uncertainty in Turbulence Models. ICMLA 2015: 813-818
Coauthor Index
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