5 citations · 5 across the 4 of their papers we have counts for
5 papers · 1 filter
MixINN: Accelerating Plant Breeding by Combining Mixed Models and Deep Learning for Interaction Prediction
Aike Potze, Fred van Eeuwijk, Ioannis N. Athanasiadis
Plant breeding underpins global food security through incremental, accumulating improvements in crop yield, quality and sustainability, achieved via repeated cycles of crop ranking…
Positive-Unlabeled Learning for Control Group Construction in Observational Causal Inference
Ilias Tsoumas, Dimitrios Bormpoudakis, Vasileios Sitokonstantinou +4
In causal inference, whether through randomized controlled trials or observational studies, access to both treated and control units is essential for estimating the effect of a tre…
Hybrid Phenology Modeling for Predicting Temperature Effects on Tree Dormancy
Ron van Bree, Diego Marcos, Ioannis Athanasiadis
Biophysical models offer valuable insights into climate-phenology relationships in both natural and agricultural settings. However, there are substantial structural discrepancies a…
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…
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…