متابعة
Brayden Bekker
Brayden Bekker
BYU, Brigham Young University, Physics
بريد إلكتروني تم التحقق منه على byu.edu
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
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
1372019
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
Structural Determination of a Cubic Ni-Rich Phase in Hf-Ni-Ti‏
J Meziere, S Mohan, B Bekker, H Oliver, L Cvetko, AP Stebner, GLW Hart‏
Available at SSRN 4949620, 0‏
General machine-learning surrogate models for materials prediction‏
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...‏
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مقالات 1–13