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Physics to Machine learning and machine leaning back to physics
Presenter
- Pierre Gentine
November 1, 2022
IMSI
Using data-informed methods towards an improved understanding and representation of atmospheric gravity waves
Presenter
- Aditi Sheshadri
November 1, 2022
IMSI
Combining Stochastic Parameterized Reduced Order Models with Machine Learning for Data Assimilation and Uncertainty Quantification with Partial Observations
Presenter
- Nan Chen
October 31, 2022
IMSI
Explainable AI (XAI) for Climate Science: Detection, Prediction and Discovery
Presenter
- Elizabeth Barnes
October 31, 2022
IMSI
Artificial intelligence with uncertainty quantification can plug gaps in climate science and inform multi sector resilience
Presenter
- Auroop Ganguly
October 31, 2022
IMSI
Using autoencoders as generative models to create forecast ensembles for data assimilation
Presenter
- Ian Grooms
October 31, 2022
IMSI
Accelerated Parametric Uncertainty Quantification and Optimal Data Acquisition in an Idealized Global Atmosphere Model
Presenter
- Oliver Dunbar
October 31, 2022
IMSI
Improving Tropical Climate Simulations with Stochastic Models for Clouds
Presenter
- Boualem Khouider
March 3, 2021
IMSI
Physics Guided Machine Learning: A New Paradigm for Modeling Dynamical Systems
Presenter
- Vipin Kumar
November 6, 2018
IPAM
Towards Spatial Data Science for Smart Agriculture Big Data
Presenter
- Shashi Shekhar
October 26, 2017
IMA
Blending physics and machine learning to improve climate projections
Presenter
- Laure Zanna
October 9, 2020
IMSI
