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Found 4 papers, 2 papers with code
Climate-mediated shifts in temperature fluctuations promote extinction risk
When integrated into empirically-parameterized mathematical models that simulate the dynamical and cumulative effects of thermal stress on the performance of 38 global ectotherm species, the projected spatiotemporal changes in temperature fluctuations are expected to give rise to complex regional changes in population abundance and stability over the course of the 21st century.
Explainable deep learning for insights in El Niño and river flows
The El Ni\~no Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections.
A framework for deep learning emulation of numerical models with a case study in satellite remote sensing
A difficult test for deep learning-based emulation, which refers to function approximation of numerical models, is to understand whether they can be comparable to traditional forms of surrogate models in terms of computational efficiency while simultaneously reproducing model results in a credible manner.
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images
Machine learning has proven to be useful in classification and segmentation of images.
