关于这个播客 🔗
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.
更新频率:
every 51 days
平均音频长度:
22 minutes
英语
美国
10 集
自从 2018年6月30日
episodic
最新一集 🔗
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:...
以前的节目 🔗
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 Candi...
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....
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-...
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...
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/Phy...
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.
免责声明: 本页面嵌入的播客和封面图片来自 Stanford Materials Computation and Theory Group, Qian Yang's lab at the University of Connecticut,归其所有者所有,与 Listen Notes, Inc. 无关联,也未获得 Listen Notes, Inc. 背书。
认领这个播客
Why to claim podcasts?
If you are a podcaster, the best way to manage your podcasts on Listen Notes is by claiming your Listen Notes
podcast pages.
It is a great, free way to engage the podcast community and increase the visibility of your podcasts.
After claiming your Listen Notes podcast pages, you will be able to:
✓
Manually refresh the RSS feed to sync up
✓
Get a verified badge (
✓
) alongside with your podcast name on Listen Notes
✓
Post 分类广告 for sponsorship,
guests, co-hosts,
cross-promotion...
✓
Respond to listener comments on Listen Notes
✓
Use speech-to-text techniques to transcribe your show and
edit transcripts
✓
Improve the presence of your podcasts, e.g., self-service
播客创作者访谈...
✓
If you share your Listen Notes page and at-mention @ListenNotes
on X (formerly Twitter),
我们的官方 X(原 Twitter)账户 will retweet to promote
your show to our followers.
Coming soon:
◯ Self-service promotion on Listen Notes
◯ Track your podcast stats on Listen
Notes, e.g., listens, page
views...
◯ Manage episodes