Boosting the discovery rate of energy materials using deep learning
Master of Science in Engineering Physics
2020
M. Larmuseau
The Fe-Si phase diagram: from electrical steel to the planet Mercury
Heredity in materials science: unravelling the electronic quantum genome
Charting the magnetocrystalline anisotropy energy in iron space
Boosting the discovery rate of energy materials using deep learning
How many materials are left to discover? An exploration of quaternary space
ISBN/ISSN:
Talk
Conference / event / venue
International Workshop on Machine Learning for Materials Science 2018
Aalto, Finland
Thursday, 3 May, 2018 to Friday, 4 May, 2018
Accelerating materials screening with machine learning: The case study of silicon
ISBN/ISSN:
Talk
Conference / event / venue
34th winter school in theoretical chemistry: Machine Learning in Theoretical Chemistry
Helsinki, Finland
Monday, 10 December, 2018 to Thursday, 13 December, 2018
Machine learning and materials science: ab initio screening to microstructure analysis
ISBN/ISSN:
Poster
Conference / event / venue
34th winter school in theoretical chemistry: Machine Learning in Theoretical Chemistry
Helsinki, Finland
Monday, 10 December, 2018 to Thursday, 13 December, 2018
Speeding up materials discovery and design: from high-throughput screening to machine learning
ISBN/ISSN:
Invited talk
Conference / event / venue
MSNANO-18
Faisalabad, Pakistan
Monday, 19 February, 2018 to Tuesday, 20 February, 2018
How many materials are left to discover? An exploration of quaternary space
19
ISBN/ISSN:
Talk
Conference / event / venue
ML4MS Conference
Espoo, Finland
Thursday, 3 May, 2018 to Friday, 4 May, 2018
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