[Office of Basic Energy Sciences (BES)] Roundtable on Producing and Managing Large Scientific Data with Artificial Intelligence and Machine Learning

Author:

Ratner Daniel1,Sumpter Bobby2,Alexander Frank3,Billings Jay2,Coffee Ryan1,Cousineau Sarah2,Denes Peter4,Doucet Mathieu2,Foster Ian5,Hexemer Alex4,Hidas Dean3,Huang Xiaobiao1,Kalinin Sergei2,Kiran Mariam4,Kusne A.6,Mehta Apurva1,Ramirez-Cuesta Anibal (Timmy)2,Sankaranarayanan Subramanian5,Scott Mary4,Stevens Mark7,Sun Yipeng5,Thayer Jana1,Toby Brian5,Ushizima Daniela4,Vasudevan Rama2,Wilkins Stuart3,Yager Kevin3

Affiliation:

1. SLAC National Accelerator Lab., Menlo Park, CA (United States)

2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

3. Brookhaven National Lab. (BNL), Upton, NY (United States)

4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

5. Argonne National Lab. (ANL), Argonne, IL (United States)

6. National Institute of Standards and Technology

7. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Publisher

Office of Scientific and Technical Information (OSTI)

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Learning Identification of Organic Compounds Using Visible Light;The Journal of Physical Chemistry A;2023-03-06

2. Molecular-Modified Photocathodes for Applications in Artificial Photosynthesis and Solar-to-Fuel Technologies;Chemical Reviews;2022-09-29

3. ASAP;Proceedings of the 36th ACM International Conference on Supercomputing;2022-06-28

4. The case for data science in experimental chemistry: examples and recommendations;Nature Reviews Chemistry;2022-04-21

5. Introduction;Machine Learning-Augmented Spectroscopies for Intelligent Materials Design;2022

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