The Differentiable Ecosystem Model (a hybrid, physics-informed machine learning system for ecosystem modeling). This release contains example codes and datasets similar to those used to produce some work in the following paper:
Aboelyazeed, D., Xu, C., Hoffman, F. M., Liu, J., Jones, A. W., Rackauckas, C., Lawson, K. E., and Shen, C.: A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: Demonstration with photosynthesis simulations, Biogeosciences (Accepted, 2023) [preprint] https://doi.org/10.5194/bg-2022-211.
Please cite this paper if the code is helpful to you.
Please read this Instruction file which includes detailed instructions for running the released codes
If you have any questions for this code release, feel free to contact us by dmf5963@psu.edu (Doaa Aboelyazeed) or cshen@engr.psu.edu (Chaopeng Shen)