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View article: Downscaling with the foundation model AtmoRep
Downscaling with the foundation model AtmoRep Open
In recent years, deep neural networks (DNN) to enhance the resolution of meteorological data, known as statistical downscaling, have surpassed classical statistical methods that have been developed previously with respect to several valida…
View article: AtmoRep: large scale representation learning for atmospheric dynamics
AtmoRep: large scale representation learning for atmospheric dynamics Open
The atmosphere affects humans in a multitude of ways, from loss of lives due to adverse weather effects to long-term social and economic impacts. Very recently, AI-based models have shown tremendous potential in reducing the computational …
View article: Attention maps for atmorep: studying large-scale representation learning of atmospheric dynamics
Attention maps for atmorep: studying large-scale representation learning of atmospheric dynamics Open
With the escalating threat of climate change, innovative technological solutions have become imperative. In this light, we introduce "AtmoRep," a cutting-edge, large-scale transformer designed specifically for the representation learning o…
View article: AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning
AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning Open
The atmosphere affects humans in a multitude of ways, from loss of life due to adverse weather effects to long-term social and economic impacts on societies. Computer simulations of atmospheric dynamics are, therefore, of great importance …
View article: AtmoRep: Large Scale Representation Learning for Atmospheric Data
AtmoRep: Large Scale Representation Learning for Atmospheric Data Open
The AtmoRep project asks if one can train one neural network that represents and describes all atmospheric dynamics. AtmoRep’s ambition is hence to demonstrate that the concept of large-scale representation learning, whose principle …
View article: Thin and edgeless sensors for ATLAS pixel detector upgrade
Thin and edgeless sensors for ATLAS pixel detector upgrade Open
To cope with the harsh environment foreseen at the high luminosity conditions\nof HL- LHC, the ATLAS pixel detector has to be upgraded to be fully efficient\nwith a good granularity, a maximized geometrical acceptance and an high read\nout…