À PROPOS DE CE PODCAST 🔗
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.
Fréquence de mise à jour:
every 51 days
Durée audio moyenne:
22 minutes
Anglais
États-Unis
10 épisodes
depuis 30 juin 2018
episodic
DERNIER ÉPISODE 🔗
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: P…
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ÉPISODES PRÉCÉDENTS 🔗
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 Candida…
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. P…
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…
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 v…
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., Gaussianapproximation potentials: the accuracy of quantum mechanics, without the electrons. Physical Review Letters, doi:10.1103/PhysR…
Our guest on this episode is Professor Evan J. Reed from Stanford University.
Our guest on this episode is Dr. Ekin Doğuş Çubuk from Google Brain.
Our guest on this episode is Professor Kieron Burke from the University of California, Irvine.
Start here for a brief introduction to this podcast!
Avertissement: Le podcast et les illustrations intégrés sur cette page proviennent de Stanford Materials Computation and Theory Group, Qian Yang's lab at the University of Connecticut, qui est la propriété de son propriétaire et n'est ni affilié ni approuvé par Listen Notes, Inc.
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