Materials and Megabytes
Exploring the development of machine learning for materials science, physics, and chemistry applications through conversation with researchers at the forefront of this growing interdisciplinary field. Brought to you in collaboration by the Stanford Materials Computation and Theory Group and Qian Yang's lab at the University of Connecticut.
Materials and Megabytes
Gábor Csányi (Season 2, Ep. 1)
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Qian Yang / Gábor Csányi
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Season 2
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Episode 1
Our guest on this episode is Professor Gábor Csányi from the University of Cambridge.
Some relevant papers:
- Bartok, A. P., Payne, M. C., Kondor, R., and Csanyi, G., Gaussian
approximation potentials: the accuracy of quantum mechanics, without the electrons. Physical Review Letters, doi:10.1103/PhysRevLett.104.136403
(2010) - Bartok, A. P., Kondor, R., and Csanyi, G., On representing chemical environments. Phys. Rev. B, doi:10.1103/PhysRevB.87.184115 (2013)
- Braams, B. J., and Bowman, J. M., Permutationally invariant potential energy surfaces in high dimensionality. International Reviews in Physical Chemistry, doi:10.1080/01442350903234923 (2009)