J. E. Gubernatis

Santa Fe Institute — United States

Physics and Astronomy · Physical Sciences

45h-index10.8kcitations273works0.02yr avg
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Research Topics

Physics of Superconductivity and Magnetism(67), Theoretical and Computational Physics(50), Quantum and electron transport phenomena(46), Advanced Chemical Physics Studies(35), Ultrasonics and Acoustic Wave Propagation(22)

Publications273 total

Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods
Synthesis lectures on materials and optics·2020· 10 cited
The voice of physics in Africa
Bulletin of the American Physical Society·2020
Some Closing Thoughts
Synthesis lectures on materials and optics·2020
Materials Representations
Synthesis lectures on materials and optics·2020
Multi-Objective Learning
Synthesis lectures on materials and optics·2020
Introduction
Synthesis lectures on materials and optics·2020· 1 cited
Learning with Small Databases
Synthesis lectures on materials and optics·2020
Multi-Fidelity Learning
Synthesis lectures on materials and optics·2020
Learning with Large Databases
Synthesis lectures on materials and optics·2020
Data-Based Methods for Materials Design and Discovery
Synthesis lectures on materials and optics·2020· 4 cited
The Monte Carlo Method:From Then to Now
Notices of the American Mathematical Society·2019
Machine learning in materials design and discovery: Examples from the present and suggestions for the future
Physical Review Materials·2018· 188 citedOpen Access
GovMath
Notices of the American Mathematical Society·2018Open Access
Predictions of new <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi mathvariant="italic">AB</mml:mi><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:mrow></mml:math> perovskite compounds by combining machine learning and density functional theory
Physical Review Materials·2018· 179 citedOpen Access
Predictions of New ABO3 Perovskite Compounds by Combining Machine Learning and Density Functional Theory
Bulletin of the American Physical Society·2018· 36 cited
Multi-objective Optimization for Materials Discovery via Adaptive Design
Scientific Reports·2018· 163 citedOpen Access
Double Perovskites Gap Data
Figshare·2018Open Access
Importance of Feature Selection in Machine Learning and Adaptive Design for Materials
Springer series in materials science·2018· 32 cited
Importance of Feature Selection in the Adaptive Design of Materials by Machine Learning
Figshare·2017Open Access
Machine Learning of ABO$_3$ Crystalline Compounds
Bulletin of the American Physical Society·2017
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Frequent Co-authors

Turab Lookman(8), Naoki Kawashima(7), Shiwei Zhang(6), J. Carlson(5), Gerardo Ortíz(5), D. J. Scalapino(4), Ghanshyam Pilania(4), Mark Jarrell(3), Steven R. White(3), R. Sugar(3), Eugene Loh(3), R. N. Silver(3), D.S. Sivia(3), Emanuel Knill(3), Eytan Domany(3), J. A. Krumhansl(3), Prasanna V. Balachandran(3), Richard T. Scalettar(2), Rolando D. Somma(2), Raymond Laflamme(2)