21 citations · 40 across the 20 of their papers we have counts for
5 papers · 1 filter
Set Prediction for Next-Day Active Fire Forecasting
Yuchen Bai, Georgios Athanasiou, Xin Yu +4
Accurate next-day active fire forecasts can support early warning, disaster response, forest risk assessment, and downstream estimation of fire-related carbon emissions. Existing m…
Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Spyros Kondylatos, Nikolas Papadopoulos, Gustau Camps-Valls +1
Wildfires are among the most severe natural hazards, posing a significant threat to both humans and natural ecosystems. The growing risk of wildfires increases the demand for forec…
Wildfire spread forecasting with Deep Learning
Nikolaos Anastasiou, Spyros Kondylatos, Ioannis Papoutsis
Accurate prediction of wildfire spread is crucial for effective risk management, emergency response, and strategic resource allocation. In this study, we present a deep learning (D…
Probabilistic Machine Learning for Noisy Labels in Earth Observation
Spyros Kondylatos, Nikolaos Ioannis Bountos, Ioannis Prapas +3
Label noise poses a significant challenge in Earth Observation (EO), often degrading the performance and reliability of supervised Machine Learning (ML) models. Yet, given the crit…
Causal Graph Neural Networks for Wildfire Danger Prediction
Shan Zhao, Ioannis Prapas, Ilektra Karasante +4
Wildfire forecasting is notoriously hard due to the complex interplay of different factors such as weather conditions, vegetation types and human activities. Deep learning models s…