On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory by Guignard, Fabian
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On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory by Guignard, Fabian

On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory

Springer
Price:
$179.99

Description


Author: Fabian Guignard
Publisher: Springer
Published: 03/13/2023
Pages: 158
Binding Type: Paperback
Weight: 0.57lbs
Size: 9.21h x 6.14w x 0.38d
ISBN13: 9783030952334
ISBN10: 3030952339
BISAC Categories:
- Science | General
- Computers | Computer Simulation
- Technology & Engineering | Power Resources | Alternative & Renewable

About the Author
Dr. Fabian Guignard is an environmental data scientist born in 1983 in Switzerland. He received a M.S. degree in Mathematics from Ecole Polytechnique Fédérale de Lausanne (EPFL, Switzerland) in 2015 and a Ph.D. in Environmental Sciences from the University of Lausanne (UNIL, Switzerland) in 2021. His main research interests lie at the intersection of applied mathematics and computer science, including machine learning, uncertainty quantification and their applications to environmental spatio-temporal statistics.