Nowcasting is an observation-based method that uses the current state of the atmosphere to forecast future weather conditions over several hours. Recent studies have shown the promising potential of using deep learning models for precipitation nowcasting. In this paper, novel deep generative models are proposed for precipitation nowcasting. These models are equipped with extreme-value losses to more reliably predict extreme precipitation events. The proposed deep generative model contains a Vector Quantization Generative Adversarial Network and a Transformer ("VQGAN + Transformer"). For enhanced modeling and forecasting of extreme events, Extreme Value Loss (EVL) is incorporated in the autore-gressive Transformer. The numerical results show that the proposed model achieves comparable performance with the state-of-the-art conventional nowcasting method PySTEPS for predicting nominal values. By incorporating an EVL, the proposed model yields more accurate nowcasting of extreme precipitation.@en

We typically search for images by keywords, e.g., when looking for images of apples, we would enter the word “apple” as query. However, there are limitations. For example, if users input keywords in a specific language, then they may miss results labeled in other languages. Moreover, users may have an image of the object they want to obtain more information about, e.g., a landmark, but they may not know the name of it. In such scenario, word-based search is not adequate, while imagebased search would be ideally suited. These needs drive us to develop a purely content-based image search engine, meaning that users can search images with an image as query. Motivated by this use case with numerous applications, in this paper we propose and validate an image query based search engine...@en

Extreme precipitation usually leads to substantial impacts. Floods in the Netherlands, Belgium and Germany in the summer of 2021 have caused loss of lives, destruction of infrastructures, and long-term effect on economics. To avoid such disasters, it is important to develop a reliable and accurate method to predict heavy rain. @en