M. Ayoub Chettouh
First year PhD Researcher at the Max Planck Institute for Biogeochemistry with a background in theoretical physics. Julia user since 2017.
Research Summary: Parameterizing physical and other models using neural networks, applications to soil science.
Session
10-02
16:45
3min
End-to-End Parameter Learning and applications to soil science.
M. Ayoub Chettouh
In this presentation, we showcase Parameter-Learning in soil carbon modeling, a scientific machine learning paradigm where a process-based model is parameterized through the use of a neural network. This enables us to learn latent soil properties from soil carbon data, leveraging the Julia’s ML and auto-differentiation ecosystems. The resulting hybrid model is more explainable through the latent variables, and more robust as it is constrained to a process-based model.
Posters
Coffee room