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2020 – today
- 2023
[j2]Kamal Choudhary
, Ramya Gurunathan, Brian DeCost, Adam J. Biacchi:
AtomVision: A Machine Vision Library for Atomistic Images. J. Chem. Inf. Model. 63(6): 1708-1722 (2023)- [i8]Phillip M. Maffettone, Daniel B. Allan, Stuart I. Campbell, Matthew R. Carbone, Thomas A. Caswell, Brian L. DeCost, Dmitri Gavrilov, Marcus D. Hanwell, Howie Joress, Joshua K. Lynch, Bruce Ravel, Stuart B. Wilkins, Jakub Wlodek, Daniel Olds:
Self-driving Multimodal Studies at User Facilities. CoRR abs/2301.09177 (2023) - [i7]Francesca Tavazza, Kamal Choudhary, Brian DeCost:
Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison. CoRR abs/2310.13136 (2023) - [i6]A. Gilad Kusne, Austin McDannald, Brian DeCost:
Learning material synthesis-process-structure-property relationship by data fusion: Bayesian Coregionalization N-Dimensional Piecewise Function Learning. CoRR abs/2311.06228 (2023) - 2021
- [i5]Francesca Tavazza, Brian DeCost, Kamal Choudhary:
Uncertainty Prediction for Machine Learning Models of Material Properties. CoRR abs/2107.07997 (2021) - [i4]A. Gilad Kusne, Austin McDannald, Brian L. DeCost, Corey Oses, Cormac Toher, Stefano Curtarolo, Apurva Mehta, Ichiro Takeuchi:
Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping. CoRR abs/2111.07478 (2021) - 2020
- [j1]Brian DeCost, Jason Hattrick-Simpers, Zachary Trautt, Aaron Gilad Kusne, Eva Campo, Martin Green:
Scientific AI in materials science: a path to a sustainable and scalable paradigm. Mach. Learn. Sci. Technol. 1(3): 33001 (2020)
2010 – 2019
- 2018
- [i3]Brian L. DeCost, Toby Francis, Elizabeth A. Holm:
High throughput quantitative metallography for complex microstructures using deep learning: A case study in ultrahigh carbon steel. CoRR abs/1805.08693 (2018) - [i2]Felipe Oviedo, Zekun Ren, Shijing Sun, Charlie Settens, Zhe Liu, Noor Titan Putri Hartono, Ramasamy Savitha, Brian L. DeCost, Siyu I. P. Tian, Giuseppe Romano, Aaron Gilad Kusne, Tonio Buonassisi:
Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks. CoRR abs/1811.08425 (2018) - 2017
- [i1]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)
Coauthor Index
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