Find the EGU on

Tag your tweets with #EGU18

IE4.1/NP4.3/AS5.13/CL5.18/ESSI2.3/GD10.6/HS3.7/NH11.14/SM7.03

Big data and machine learning in geosciences (co-organized)
Convener: Mikhail Kanevski  | Co-Conveners: Peter Baumann , Philip Brown , Reik Donner , Sandro Fiore , Kwo-Sen Kuo , Rosa Lasaponara , Morris Riedel , Karsten Steinhaeuser , Nicolas Younan 
Orals
 / Mon, 09 Apr, 10:30–12:00  / 13:30–17:00  / Room N2
Posters
 / Attendance Mon, 09 Apr, 17:30–19:00  / Hall X3
Add this session to your Personal programme

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and extremely detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with and methodological approaches towards automatically inferring relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:

• Dimensionality and complexity of big data sets
• Data mining and machine learning
• Deep learning in geo- and environmental sciences
• Visualization and visual analytics of big data
• Complex networks and graph analysis
• Informatics and data science