67 citations · 152 across the 31 of their papers we have counts for
13 papers · 1 filter
Climate Variability Modulates the Impact of Price Spikes on Food Insecurity
Jordi Cerdà-Bautista, Vasileios Sitokonstantinou, Homer Durand +3
Climate variability influences whether a market disruption escalates into a food crisis, yet broad climate patterns like El Niño, tracked months before they alter hydro-climatic co…
Credit Access is Associated with Improved Food Security in the Horn of Africa
Jordi Cerdà-Bautista, Vasileios Sitokonstantinou, José Manuel Veiga López-Peña +3
The intensification of climate change poses a growing threat to food security, especially in vulnerable communities. This study employs an observational machine-learning framework…
Optimization Geometry of Equivalent Brownian RKHS Representations
Mahdi Mohammadigohari, Gustau Camps-Valls
Equivalent finite parameterizations can represent the same functions and intrinsic norm yet induce different optimization algorithms. We study this effect in a controlled finite Br…
Physically consistent and uncertainty-aware learning of spatiotemporal dynamics
Qingsong Xu, Jonathan L Bamber, Nils Thuerey +5
Accurate long-term forecasting of spatiotemporal dynamics remains a fundamental challenge across scientific and engineering domains. Existing machine learning methods often neglect…
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…
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…
Explainable Earth Surface Forecasting under Extreme Events
Oscar J. Pellicer-Valero, Miguel-Ángel Fernández-Torres, Chaonan Ji +2
With climate change-related extreme events on the rise, high dimensional Earth observation data presents a unique opportunity for forecasting and understanding impacts on ecosystem…
Causal machine learning for sustainable agroecosystems
Vasileios Sitokonstantinou, Emiliano Díaz Salas Porras, Jordi Cerdà Bautista +8
In a changing climate, sustainable agriculture is essential for food security and environmental health. However, it is challenging to understand the complex interactions among its…
DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes
Chaonan Ji, Tonio Fincke, Vitus Benson +12
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show prom…
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…
Causal hybrid modeling with double machine learning
Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais +2
Hybrid modeling integrates machine learning with scientific knowledge to enhance interpretability, generalization, and adherence to natural laws. Nevertheless, equifinality and reg…
Causality and Explainability for Trustworthy Integrated Pest Management
Ilias Tsoumas, Vasileios Sitokonstantinou, Georgios Giannarakis +5
Pesticides serve as a common tool in agricultural pest control but significantly contribute to the climate crisis. To combat this, Integrated Pest Management (IPM) stands as a clim…
Assessing the Causal Impact of Humanitarian Aid on Food Security
Jordi Cerdà-Bautista, José María Tárraga, Vasileios Sitokonstantinou +1
In the face of climate change-induced droughts, vulnerable regions encounter severe threats to food security, demanding urgent humanitarian assistance. This paper introduces a caus…