Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Baird, Sterling G."'
Autor:
Choudhary, Kamal, Wines, Daniel, Li, Kangming, Garrity, Kevin F., Gupta, Vishu, Romero, Aldo H., Krogel, Jaron T., Saritas, Kayahan, Fuhr, Addis, Ganesh, Panchapakesan, Kent, Paul R. C., Yan, Keqiang, Lin, Yuchao, Ji, Shuiwang, Blaiszik, Ben, Reiser, Patrick, Friederich, Pascal, Agrawal, Ankit, Tiwary, Pratyush, Beyerle, Eric, Minch, Peter, Rhone, Trevor David, Takeuchi, Ichiro, Wexler, Robert B., Mannodi-Kanakkithodi, Arun, Ertekin, Elif, Mishra, Avanish, Mathew, Nithin, Baird, Sterling G., Wood, Mitchell, Rohskopf, Andrew Dale, Hattrick-Simpers, Jason, Wang, Shih-Han, Achenie, Luke E. K., Xin, Hongliang, Williams, Maureen, Biacchi, Adam J., Tavazza, Francesca
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leade
Externí odkaz:
http://arxiv.org/abs/2306.11688
Autor:
Maffettone, Phillip M., Friederich, Pascal, Baird, Sterling G., Blaiszik, Ben, Brown, Keith A., Campbell, Stuart I., Cohen, Orion A., Collins, Tantum, Davis, Rebecca L., Foster, Ian T., Haghmoradi, Navid, Hereld, Mark, Jung, Nicole, Kwon, Ha-Kyung, Pizzuto, Gabriella, Rintamaki, Jacob, Steinmann, Casper, Torresi, Luca, Sun, Shijing
Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and so
Externí odkaz:
http://arxiv.org/abs/2304.11120
Expensive-to-train deep learning models can benefit from an optimization of the hyperparameters that determine the model architecture. We optimize 23 hyperparameters of a materials informatics model, Compositionally-Restricted Attention-Based Network
Externí odkaz:
http://arxiv.org/abs/2203.12597
Experimentally [1-38] and computationally [39-50] validated machine learning (ML) articles are sorted based on the size of the training data: 1-100, 101-10000, and 10000+ in a comprehensive set summarizing legacy and recent advances in the field. The
Externí odkaz:
http://arxiv.org/abs/2202.02380
We introduce the Voronoi fundamental zone octonion interpolation framework for grain boundary (GB) structure-property models and surrogates. The VFZO framework offers an advantage over other five degree-of-freedom based property interpolation methods
Externí odkaz:
http://arxiv.org/abs/2104.06575
Akademický článek
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Publikováno v:
In Computational Materials Science September 2023 228
Publikováno v:
In Computational Materials Science May 2023 224
Akademický článek
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Autor:
Johnson, Oliver K., Homer, Eric R., Fullwood, David T., Page, David E., Varela, Kathryn F., Baird, Sterling G.
Publikováno v:
In Acta Materialia 15 August 2021 215