2 papers
cs.CE2026
Deep-learning surrogate crop modelling for scalable seasonal-to-climate crop-risk assessment
Odysseas Vlachopoulos, Andrej Ceglar, Juerg Luterbacher +3
Anticipating climate-related crop stress requires crop-risk information that is spatially explicit, probabilistic and fast enough for large seasonal forecast and climate-scenario e…
q-fin.GN2020
Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package
Matteo Zampieri, Andrea Toreti, Andrej Ceglar +2
This paper presents a Python object-oriented software and code to compute the annual production resilience indicator. The annual production resilience indicator can be applied to d…