Julia Ling

Publication Activity (10 Years)

Years Active: 2015-2020
Publications (10 Years): 10

Top Topics

Prior Probabilities

Machine Learning

Scientific Computing

Top Venues

J. Comput. Phys.

Publications

Pedro M. Milani, Julia Ling, John K. Eaton
Turbulent scalar flux in inclined jets in crossflow: counter gradient transport and deep learning modelling. CoRR (2020)
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 (2019)
Yoolhee Kim, Edward Kim, Erin Antono, Bryce Meredig, Julia Ling
Machine-learned metrics for predicting the likelihood of success in materials discovery. CoRR (2019)
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 (2019)
Pedro M. Milani, Julia Ling, John K. Eaton
Generalization of machine-learned turbulent heat flux models applied to film cooling flows. CoRR (2019)
Maxwell L. Hutchinson, Erin Antono, Brenna M. Gibbons, Sean Paradiso, Julia Ling, Bryce Meredig
Overcoming data scarcity with transfer learning. CoRR (2017)
Julia Ling, Maxwell Hutchinson, Erin Antono, Brian DeCost, Elizabeth A. Holm, Bryce Meredig
Building Data-driven Models with Microstructural Images: Generalization and Interpretability. CoRR (2017)
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)
Julia Ling, Reese E. Jones, Jeremy A. Templeton
Machine learning strategies for systems with invariance properties. J. Comput. Phys. 318 (2016)
Julia Ling
Using Machine Learning to Understand and Mitigate Model Form Uncertainty in Turbulence Models. ICMLA (2015)