View source for Machine learning related to GEOS-Chem

All users interested in the use of Machine Learning within the GEOS-Chem community are encouraged to subscribe to the machine learning email list (click on the link in the [[#Contact information|contact information section]] below).

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!width="300px" bgcolor="#CCCCCC"|Machine Learning in GEOS-Chem support
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*[http://www.york.ac.uk/chemistry/staff/academic/d-g/evansm/ Mat Evans]
*[https://sciences.gsfc.nasa.gov/sed/bio/christoph.a.keller Christoph Keller]

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!bgcolor="#CCCCCC"|GEOS-Chem Machine Learning email list
|<tt>geos-chem-ml [at] g.harvard.edu</tt>

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!bgcolor="#CCCCCC"|To subscribe to email list
|Either
*Send an email to <tt>geos-chem-ml+subscribe [at] g.harvard.edu</tt>
Or
*Go to the [https://groups.google.com/a/g.harvard.edu/forum/#!forum/geos-chem-ml GEOS-Chem Machine Learning]
*Click on '''Subscribe to this group'''

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!bgcolor="#CCCCCC"|To unsubscribe from email list
|Either
*Send an email to <tt>geos-chem-ml+unsubscribe [at] g.harvard.edu</tt>
Or
*Go to the [https://groups.google.com/a/g.harvard.edu/forum/#!forum/geos-chem-ml GEOS-Chem Machine Learning]
*Click on the '''My Settings''' button
*Click on '''Leave this group'''

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== GEOS-Chem Machine Learning Publications ==
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!width="150px"|Contact Persons
!width="600px"|Paper
!width="100px"|Date Added
|-
|[mailto:christoph.a.keller@nasa.gov Christoph Keller] <br> [mailto:mat.evans@york.ac.uk Mat Evans]
|[https://www.geosci-model-dev.net/12/1209/2019/gmd-12-1209-2019.html Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10]
|14th May 2019
|-
|[mailto:samsilva@mit.edu Sam Silva] <br> [mailto:heald@mit.edu Colette Heald]
|[https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GL081049 A Deep Learning Parameterization for Ozone Dry Deposition Velocities]
|14th May 2019
|-
|[mailto:tomas.sherwen@york.ac.uk Tomas Sherwen] <br> [mailto:mat.evans@york.ac.uk Mat Evans]
|[https://www.earth-syst-sci-data-discuss.net/essd-2019-40/ A machine learning based global sea-surface iodide distribution]
|14th May 2019
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== Current GEOS-Chem Machine Learning Projects ==
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!width="200px"|User Group	
!width="600px"|Description	
!width="150px"|Contact Person
!width="100px"|Date Added
|-
|University of York 
|Post processing bias corrector 
|[mailto:pi517@york.ac.uk Peter Ivatt]<br>[mailto:mat.evans@york.ac.uk Mat Evans]
|14th May 2019
|-
|Duke University
|Ozone metrics predictor
|[mailto:psk9@duke.edu Prasad Kasibhatla]
|14th May 2019
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|University of York 
|Spatial and temporal concentration prediction from sparse obsevations at the ocean surface
|[mailto:tomas.sherwen@york.ac.uk Tomás Sherwen]
|14th May 2019
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== Useful resources ==
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!width="300px"|Resource
!width="600px"|Description	
|-
|[https://en.wikipedia.org/wiki/Machine_learning Wikipedia Page]
|Default Wikipedia ML launch page
|-
|[https://www.tensorflow.org Google Tensor Flow]
|Google's Machine Learning package
|-
|[https://scikit-learn.org/stable/ Scikit-Learn]
|Scikit-Learn package for machine learning in Python
|-
|[https://xgboost.readthedocs.io/en/latest/ XGboost]
| Machine learning algorithms implemented under the Gradient Boosting framework in Python
|-
|[https://lightgbm.readthedocs.io/en/latest/ GBMLight]
| Microsofts' distributed high-performance gradient boosting implementation
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== Upcoming conferences / workshops  ==
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!width="300px"|Conference
!width="600px"|Date
|-
|[https://www.rmets.org/event/atmospheric-science-conference-2019 Machine Learning in Earth Systems workshop at NCAS'/RMetS' Atmospheric Science Conference 2019]
|2-3rd July 2019
|-
|[http://users.ox.ac.uk/~phys0895/mlwc2019/index.html Machine Learning for Weather and Climate Modelling 2019]
|2-5th Sept 2019
|-
|[https://meetings.agu.org/fall-meeting-2019/ AGU Fall 2019]
|9-13th Dec 2019
|}