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Speakers: Please contact us about file upload for your slides.
Time | Speaker | Title |
11/1-4 | Conference: | Machine Learning for Climate |
11/08, 9:00am | Dmitri Kondrashov UCLA |
Data-driven stochastic climate modeling and prediction[Slides] |
11/10, 9:00am | Deborah Khider USC |
The challenges of using paleoclimate data for decadal prediction[Slides][Video][CC] |
11/15, 9:30am | Brian White UNC |
Deep learning applications for climate and weather modeling: toward improvements in speed, resolution and scenario generation[Embargoed] |
11/17, 9:30am | Andreas Gerhardus DLR |
Learning cause-and-effect relationships from time series data[Video] |
11/22, 9:30am | Bia Villas Boas Colorado School of Mines/Caltech |
From noise to signal: what surface waves can teach us about currents[Video] |
11/24, 9:00am | Raffaele Ferrari MIT |
New approaches to calibration of parameterizations of boundary layer turbulence[Video] |
11/29, 9:30am | Freddy Bouchet ENS Lyon |
Predicting extreme heat waves using rare event simulations and deep neural networks[Video] |
12/01, 9:30am | Markus Abel Ambrosys GmbH |
Symbolic regression and mathematical postprocessing for machine learning of (climate) dynamics[Video] |
12/01, 2:00pm | Martin Schultz Julich Centre |
Deep Learning for Air Quality and Weather Forecasting[Slides][Video] |
12/06, 9:30am | Julien Brajard NERSC |
Bridging observations and numerical modeling using machine learning[Video] |
12/06, 11:30am | Erik Mulder Univ. of Gronigen |
Symbiotic ocean modeling using physics-controlled Echo State Networks[Embargoed] |
12/08, 9:30am | Alex Robel Georgia Tech |
Statistical learning of climate for large ensemble ice sheet simulations[Slides][Video] |
12/13, 9:30am | Annalisa Bracco Georgia Tech |
Informal Talk: Lion fish, corals, connectivity, SSTs and d-MAPS[Video] |
12/13, 11:30am | Christian Lessig Univ. Magdeburg |
A Deep Neural Network Multigrid Solver[Slides][Video] |
12/13, 2:00pm | Henk Dijkstra Utrecht Univ. |
Machine Learning and the Physics of Climate[Video]
KITP Blackboard Lunch |
12/15, 9:30am | Yan Liu University of Southern California |
Differential Graph Neural Networks for Physics-Informed AI Models[Video] |
12/15, 2:00pm | Frank Kwasniok Exeter |
Data-driven deterministic and stochastic subgrid-scale parametrization in atmosphere and ocean models: a pattern-based approach[Embargoed] |