engleski

BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data

We present our winning solution model developed for the recent Data Challenge at the Extreme Value Analysis 2021 conference. The Data Challenge was about predicting deliberately missing parts of spatio-temporal numerical data on historical occurrences of wildfires in the United States. Our approach was developed with only a minimal set of assumptions and no specialist knowledge from the field of extreme value analysis.

Data reconstruction ; Variational autoencoder ; Convolutional neural network ; Deep learning ; Ensemble ; Extreme Value Analysis Conference challenge ; Wildfires

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