5 citations · 16 across the 9 of their papers we have counts for
8 papers · 1 filter
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…
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…
Understanding the impacts of crop diversification in the context of climate change: a machine learning approach
Georgios Giannarakis, Ilias Tsoumas, Stelios Neophytides +3
The concept of sustainable intensification in agriculture necessitates the implementation of management practices that prioritize sustainability without compromising productivity.…
Evaluating Digital Agriculture Recommendations with Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of smart farming tools. While AI-driven digital agriculture tools can offer hig…
Fuzzy clustering for the within-season estimation of cotton phenology
Vasileios Sitokonstantinou, Alkiviadis Koukos, Ilias Tsoumas +3
Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation,…
Evaluating Digital Tools for Sustainable Agriculture using Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of climate-smart farming tools. Even though AI-driven digital agriculture can o…
Pest presence prediction using interpretable machine learning
Ornela Nanushi, Vasileios Sitokonstantinou, Ilias Tsoumas +1
Helicoverpa Armigera, or cotton bollworm, is a serious insect pest of cotton crops that threatens the yield and the quality of lint. The timely knowledge of the presence of the ins…