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Brayden Bekker
Brayden Bekker
BYU, Brigham Young University, Physics
Bestätigte E-Mail-Adresse bei byu.edu
Titel
Zitiert von
Zitiert von
Jahr
Machine-learned multi-system surrogate models for materials prediction
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...
npj Computational Materials 5 (1), 51, 2019
1132019
Elemental Additions to Enhance Precipitate Formation in Superalloys
T Whitaker, B Bekker, H Oliver, G Hart
Bulletin of the American Physical Society 65, 2020
2020
Predicting γ′-Phase Stability in Co-Based Superalloys
H Oliver, C Nyshadham, B Bekker, G Hart
Bulletin of the American Physical Society 65, 2020
2020
How to Predict What to Measure
B Bekker, H Oliver, T Whitaker, G Hart
Bulletin of the American Physical Society 64, 2019
2019
Finding Ways to Stabilize Potential New Superalloys
T Whitaker, B Bekker, G Hart
Bulletin of the American Physical Society 64, 2019
2019
Accelerating superalloy discovery using moment tensor potentials
H Oliver, B Bekker, C Nyshadham, CA Leon Chinchay, G Hart
APS March Meeting Abstracts 2019, X19. 003, 2019
2019
Exploring Materials Space with Machine Learning
B Bekker, H Oliver, C Nyshadham, A Shapeev, G Hart
APS March Meeting Abstracts 2019, X19. 005, 2019
2019
General machine learning models for materials prediction
C Nyshadham, M Rupp, B Bekker, A Shapeev, T Mueller, C Rosenbrock, ...
Bulletin of the American Physical Society 63, 2018
2018
Studying Cobalt Based Superalloys with Machine Learning
B Bekker, C Nyshadham, G Hart
Bulletin of the American Physical Society 63, 2018
2018
Materials prediction using machine learning: comparing MBTR, MTP and deep learning
C Nyshadham, W Morgan, B Bekker, G Hart
APS March Meeting Abstracts 2018, E34. 011, 2018
2018
Machine Learning for Materials Discovery
B Bekker, C Nyshadham, G Hart
Bulletin of the American Physical Society 62, 2017
2017
General machine-learning surrogate models for materials prediction
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...
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