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.
Publisher
Stanford Materials Computation and Theory Group, Qian Yang's lab at the University of Connecticut
Paper Interview - Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models
We discuss the paper Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models with the author Prof. Heather J. Kulik. Papers discussed in this episode: (Main discussion) Duan, C.; Janet, J. P.; Liu, F.; Nandy, A.; Kulik, H. J. Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models. J. Chem. Theory Comput. 2019, 15 (4), 2331–2345. https://doi.org/10.1021/acs.jctc.9b00057.(More on uncertainty metr...
14 Sept 2019
Paper interview - Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data
We discuss the paper Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data with the authors Dr. Ekin Dogus Cubuk and Dr. Austin D. Sendek. Papers discussed in the episode: Cubuk, E. D.; Sendek, A. D.; Reed, E. J. Screening Billions of Candidates for Solid Lithium-Ion Conductors: A Transfer Learning Approach for Small Data. J. Chem. Phys. 2019, 150 (21), 214701. https://doi.org/10.1063/1.5093220.Sendek, A. D.; Yang, Q.; D. Cubuk, E.; N....
9 Apr 2019
Turab Lookman (Season 2, Ep.4)
Our guest on this episode is Dr. Turab Lookman from Los Alamos National Laboratory. The interview took place at the 2018 MRS Fall meeting. Relevant papers: Gubernatis, J. E.; Lookman, T., Machine Learning in Materials Design and Discovery: Examples from the Present and Suggestions for the Future. Phys. Rev. Materials 2018, 2 (12), 120301. https://doi.org/10.1103/PhysRevMaterials.2.120301.Rickman, J. M.; Lookman, T.; Kalinin, S. V., Materials Informatics: From the Atomic-Level to the Continuu...
15 Feb 2019
Patrick Riley (Season 2, Ep. 3)
Our guest on this episode is Dr. Patrick Riley from Google Accelerated Science. Some relevant papers and links: Riley, P., Practical advice for analysis of large, complex data sets. The Unofficial Google Data Science Blog, www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html (2016)Zinkevich, M., Rules of Machine Learning: Best Practices for ML Engineering. https://developers.google.com/machine-learning/guides/rules-of-ml/ (last updated Oct 2018)Wigner,...
25 Jan 2019
O. Anatole von Lilienfeld (Season 2, Ep. 2)
Our guest for this episode is Prof. Dr. O. Anatole von Lilienfeld from the University of Basel. Some relevant papers: Huang, B., and von Lilienfeld, O. A., The ‘DNA’ of Chemistry: Scalable Quantum Machine Learning with ‘Amons.’ arXiv:1707.04146, (2017)Ramakrishnan, R., Dral, P. O., Rupp, M., and von Lilienfeld, O. A., Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. Journal of Chemical Theory and Computation, doi:10.1021/acs.jctc.5b00099 (2015)Rup...
24 Jan 2019
Gábor Csányi (Season 2, Ep. 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., Permu...
3 Jul 2018
Evan J. Reed (Season 1, Ep. 3)
Our guest on this episode is Professor Evan J. Reed from Stanford University.
2 Jul 2018
Ekin Dogus Cubuk (Season 1, Ep. 2)
Our guest on this episode is Dr. Ekin Doğuş Çubuk from Google Brain.
1 Jul 2018
Kieron Burke (Season 1, Ep. 1)
Our guest on this episode is Professor Kieron Burke from the University of California, Irvine.
30 Jun 2018
Introduction (Season 1, Ep. 0)
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