{"id":902,"date":"2019-07-11T01:35:07","date_gmt":"2019-07-11T05:35:07","guid":{"rendered":"http:\/\/hydrouncertainty.org\/?p=902"},"modified":"2019-07-11T01:36:55","modified_gmt":"2019-07-11T05:36:55","slug":"agu-2019-fall-meeting-machine-learning","status":"publish","type":"post","link":"http:\/\/hydrouncertainty.org\/2019\/07\/11\/agu-2019-fall-meeting-machine-learning\/","title":{"rendered":"AGU 2019 Fall Meeting Sessions: Machine Learning"},"content":{"rendered":"\n

The Hydrologic Uncertainty Technical committee\u2019s mission<\/a> includes three \u201cbig research questions\u201d. The second is \u201cHow to reduce uncertainty in understanding, modelling, and predicting the future of coupled human-hydrologic systems?\u201d We\u2019ve put together a list of sessions that emphasizes this research problem. Machine learning provides a particular approach to this research problem – we\u2019ve put together a list of sessions that emphasizes machine learning.<\/p>\n\n\n\n

H093 – Machine Learning in Hydrologic Modeling<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/75246<\/a><\/p>\n\n\n\n

NG004 – Data Assimilation meets Machine Learning<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/77631<\/a><\/p>\n\n\n\n

IN033 – Incorporating physics and domain knowledge to\nimprove interpretability, explainability, reliability and generalization of\nMachine Learning Models (MLM) in the geosciences<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/82358<\/a><\/p>\n\n\n\n

Domain-specific problems<\/h2>\n\n\n\n

H045 – Domain-Aware Machine Learning for Subsurface\nApplications<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/85474<\/a><\/p>\n\n\n\n

H138 – Utility of Artificial Intelligence\/Machine Learning\nApproaches in Soil Hydrological Processes and Agriculture<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/74487<\/a><\/p>\n\n\n\n

H002 – Advances and Applications of Data Integration,\nInverse Methods, and Machine Learning in Hydrogeophysics<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/71766<\/a><\/p>\n\n\n\n

S015 – Extracting Information from Geophysical Signals with\nMachine Learning<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/80960<\/a><\/p>\n\n\n\n

S017 – Geophysical inversion, inference and imaging in the\nage of machine learning<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/80845<\/a><\/p>\n\n\n\n

U009 – Data Analytics and Machine Learning Innovation for\nClimate and Earth Surface Processes<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/83451<\/a><\/p>\n\n\n\n

EP027 – Machine Learning Applications in Earth Surface\nProcesses Research<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/75302<\/a><\/p>\n\n\n\n

In other fields<\/h2>\n\n\n\n

GC006 – AI and Machine Learning for Climate and Extreme\nWeather Prediction<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/81937<\/a><\/p>\n\n\n\n

A137 – Use of Machine Learning and Causal Discovery to\nAdvance Knowledge in the Atmospheric Sciences \u2013 Methods, Limitations and\nTrade-offs<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/76723<\/a><\/p>\n\n\n\n

A091 – Machine Learning for Climate Modeling and Inference<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/78836<\/a><\/p>\n\n\n\n

GC076 – Solar Radiation Monitoring and Forecast from\nSatellite Observations and Models: Physical and Machine Learning Perspectives<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/81059<\/a><\/p>\n\n\n\n

NG007 – Machine Learning in Space Weather<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/72833<\/a><\/p>\n\n\n\n

SH015 – Machine Learning and Data Assimilation as Emerging\nTools for Characterization and Forecasting of Solar Variability and Space\nWeather Events<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/80120<\/a><\/p>\n\n\n\n

P022 – Machine Learning for Planetary Science<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/78481<\/a><\/p>\n\n\n\n

OS019 – Innovation and Exploration with Machine Learning in\nOcean and Atmospheric Sciences: Global and Regional Applications<\/p>\n\n\n\n

https:\/\/agu.confex.com\/agu\/fm19\/prelim.cgi\/Session\/85463<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The Hydrologic Uncertainty Technical committee\u2019s mission includes three \u201cbig research questions\u201d. The second is \u201cHow to reduce uncertainty in understanding, modelling, and predicting the future of coupled human-hydrologic systems?\u201d We\u2019ve put together a list of sessions that emphasizes this research<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[9],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/posts\/902"}],"collection":[{"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/comments?post=902"}],"version-history":[{"count":2,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/posts\/902\/revisions"}],"predecessor-version":[{"id":904,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/posts\/902\/revisions\/904"}],"wp:attachment":[{"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/media?parent=902"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/categories?post=902"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/hydrouncertainty.org\/wp-json\/wp\/v2\/tags?post=902"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}