Materials and Megabytes
10 episodes - English - Latest episode: over 4 years ago - ★★★★★ - 5 ratingsExploring 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.
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Episodes
Paper Interview - Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models
January 13, 2020 15:00 - 22 minutes - 15.8 MBWe 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 ...
Paper interview - Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data
September 14, 2019 18:00 - 23 minutes - 16.4 MBWe 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....
Turab Lookman (Season 2, Ep.4)
April 09, 2019 19:00 - 18 minutes - 8.71 MBOur 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 Cont...
Patrick Riley (Season 2, Ep. 3)
February 15, 2019 08:00 - 24 minutes - 11.2 MBOur 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...
O. Anatole von Lilienfeld (Season 2, Ep. 2)
January 25, 2019 20:00 - 22 minutes - 10.5 MBOur 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) Rupp, M.,...
Gábor Csányi (Season 2, Ep. 1)
January 24, 2019 08:00 - 40 minutes - 18.5 MBOur 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.,...
Evan J. Reed (Season 1, Ep. 3)
July 03, 2018 07:00 - 19 minutes - 9.12 MBOur guest on this episode is Professor Evan J. Reed from Stanford University.
Ekin Dogus Cubuk (Season 1, Ep. 2)
July 02, 2018 07:00 - 28 minutes - 13 MBOur guest on this episode is Dr. Ekin Doğuş Çubuk from Google Brain.
Kieron Burke (Season 1, Ep. 1)
July 01, 2018 07:00 - 14 minutes - 6.63 MBOur guest on this episode is Professor Kieron Burke from the University of California, Irvine.
Introduction (Season 1, Ep. 0)
June 30, 2018 07:00 - 2 minutes - 1.09 MBStart here for a brief introduction to this podcast!