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Regression modelling of spatiotemporal extreme U.S. wildfires via
  partially-interpretable neural networks

Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks

16 August 2022
J. Richards
Raphael Huser
ArXivPDFHTML

Papers citing "Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks"

4 / 4 papers shown
Title
Extreme Conformal Prediction: Reliable Intervals for High-Impact Events
Extreme Conformal Prediction: Reliable Intervals for High-Impact Events
Olivier C. Pasche
Henry Lam
Sebastian Engelke
29
0
0
13 May 2025
Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events
Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events
Olivier C. Pasche
Jonathan Wider
Zhongwei Zhang
Jakob Zscheischler
Sebastian Engelke
AI4Cl
37
10
0
26 Apr 2024
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
Matthew Sainsbury-Dale
A. Zammit‐Mangion
J. Richards
Raphael Huser
28
15
0
04 Oct 2023
Insights into the drivers and spatio-temporal trends of extreme
  Mediterranean wildfires with statistical deep-learning
Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning
J. Richards
Raphael Huser
E. Bevacqua
Jakob Zscheischler
11
12
0
04 Dec 2022
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