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Explainable AI (XAI) for Climate Science: Detection, Prediction and Discovery
Presenter
- Elizabeth Barnes
October 31, 2022
IMSI
Systematically Generating Hierarchies of Machine-Learning Models, from Equation Discovery to Deep Neural Networks
Presenter
- Tom Beucler
November 4, 2022
IMSI
Integrating the spectral analysis of neural networks and nonlinear physics for explainability, generalizability, and stability
Presenter
- Pedram Hassanzadeh
November 4, 2022
IMSI
High-resolution climate modeling using coarse-scale models and reanalysis data
Presenter
- Themistoklis Sapsis
November 3, 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
Probabilistic forecast of extreme heat waves using convolutional neural networks and rare event simulations
Presenter
- Freddy Bouchet
November 2, 2022
IMSI
Extracting climate cycles from spatiotemporal data and detecting emergence and disappearance of coherent phenomena across multiple dynamic regimes
Presenter
- Gary Froyland
November 2, 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
Sampling Strategies for Training Machine Learning Emulators of Gravity Wave
Presenter
- Minah Yang
November 2, 2022
IMSI
Using autoencoders as generative models to create forecast ensembles for data assimilation
Presenter
- Ian Grooms
October 31, 2022
IMSI
Revealing the statistics of extreme events hidden in short weather forecast data
Presenter
- Justin Finkel
November 3, 2022
IMSI