Geilo Winter School 2019: Learning from Data

The availability of ever more computing power and data has led to an enormous development in methods related to data in the recent years. In this winter school, we will look at methods for using the knowledge in data to improve our computer algorithms and look at the interplay between these. The school will focus around the following topics and try to connect the dots between these interrelated fields:

• Data assimilation
• Inverse modeling and parameter estimation
• Uncertainty quantification
• Value of information
• Machine learning and artificial intelligence

Early registration: before December 5th, 2018

Late registration: before December 22nd, 2018

For detailed information, please see the web page of the Geilo Winter School.


André Brodtkorb (SINTEF / OsloMet)
Tags: Geilo Winter School, data science, data assimilation, inverse modeling, parameter estimation, uncertainty quantification, value of information, machine learning, artificial intelligence
Published Dec. 4, 2018 2:30 PM - Last modified Dec. 4, 2018 2:30 PM