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Found 5 papers, 2 papers with code
Extreme heatwave sampling and prediction with analog Markov chain and comparisons with deep learning
In addition, we show that the SWG emulator trained on 80 years of data is capable of estimating extreme return times of order of thousands of years for heatwaves longer than several days more precisely than the fit based on generalised extreme value distribution.
Probabilistic forecasts of extreme heatwaves using convolutional neural networks in a regime of lack of data
The main scientific message is that most of the time, training neural networks for predicting extreme heatwaves occurs in a regime of lack of data.
Deep Learning-based Extreme Heatwave Forecast
The present work explores the use of deep learning architectures, trained using outputs of a climate model, as an alternative strategy to forecast the occurrence of extreme long-lasting heatwaves.
Dynamical large deviations for plasmas below the Debye length and the Landau equation
We obtain a large deviation Hamiltonian that describes fluctuations and rare excursions of the empirical density, in the large plasma parameter limit.
Statistical Mechanics Chaotic Dynamics Plasma Physics
Numerical study of extreme mechanical force exerted by a turbulent flow on a bluff body by direct and rare-event sampling techniques
While the AMS algorithm does not yield significant run-time savings as compared to direct sampling, the GKTL algorithm appears to be effective to sample very efficiently extreme fluctuations of the time-averaged drag and estimate related statistics such as return times.
Computational Physics Fluid Dynamics
