6 citations · 26 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
Deep Learning for Global Wildfire Forecasting
Ioannis Prapas, Akanksha Ahuja, Spyros Kondylatos +7
Climate change is expected to aggravate wildfire activity through the exacerbation of fire weather. Improving our capabilities to anticipate wildfires on a global scale is of utter…
Deep Learning Methods for Daily Wildfire Danger Forecasting
Ioannis Prapas, Spyros Kondylatos, Ioannis Papoutsis +5
Wildfire forecasting is of paramount importance for disaster risk reduction and environmental sustainability. We approach daily fire danger prediction as a machine learning task, u…