Ctrl K

diffWOFOST

The python package diffWOFOST is a differentiable implementation of WOFOST models using torch, allowing gradients to flow through the simulations for optimization and data assimilation.

8
contributors

Cite this software

Description

The python package diffWOFOST is a differentiable implementation of WOFOST models using torch, allowing gradients to flow through the simulations for optimization and data assimilation. The documentation is available at https://wur-ai.github.io/diffWOFOST/.

Logo of diffWOFOST
Keywords
Programming language
  • Python 100%
License
Not specified
</>Source code

Contributors

IA
Ioannis Athanasiadis
Lead Applicant
Wageningen University & Research
MK
Michiel Kallenberg
Co-Applicant
Wageningen University & Research
RvB
Ron van Bree
AdW
Allard de Wit
Francesco Nattino
Senior Research Software Engineer
Netherlands eScience Center
Yifat Dzigan
Yifat Dzigan
Section Head
Netherlands eScience Center

Related projects

DeltaCrop

From Theory to Gradients: Crop Growth Models for the AI era

Updated 12 months ago
In progress