Machine learning for approximating sub-grid physics in electromagnetic geophysics

Berkeley Statistics and Machine Learning Forum

ML&Sci Forum

September 23, 2019
1:30pm to 2:30pm
190 Doe Library
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This week's meeting will be led by Lindsey Heagy from the Department of Statistics, who will tell us about her work on using machine learning for approximating sub-grid physics in electromagnetic geophysics. Lindsey is an expert in computational geophysics, using electromagnetic measurements to probe the earth by solving massive inverse problems. She will tell us about the challenges in modelling the physics involved in these EM measurements, and how machine learning can help to build the fast and accurate forward models required by the inference algorithm. Full details about this meeting will be posted here:

The Berkeley Statistics and Machine Learning Forum meets biweekly to discuss current applications across a wide variety of research domains and software methodologies. Hosted by UC Berkeley Physics Professor and BIDS Senior Fellow Uros Seljak, these active sessions bring together domain scientists, statisticians and computer scientists who are either developing state-of-the-art methods or are interested in applying these methods in their research. Practical questions about the meetings can be directed to BIDS Fellow Francois Lanusse.  All interested members of the UC Berkeley and LBL communities are welcome and encouraged to attend. To receive email notifications about the meetings and upvote papers for discussion, please register here.


Lindsey Heagy

UC Berkeley Statistics