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Patrick Chatain

patrick.chatain@mila.quebec
Maîtrise recherche - McGill University
Superviseur⋅e principal⋅e
Adam M. Oberman

Publications

Deep PDE Solvers for Subgrid Modelling and Out-of-Distribution Generalization
Patrick Chatain
Adam M. Oberman
2023-10-31
NeurIPS.cc/2023/Workshop/DLDE (poster)
openreview.net
openreview.net
Deep PDE Solvers for Subgrid Modelling and Out-of-Distribution Generalization
Patrick Chatain
Adam M. Oberman
Climate and weather modelling (CWM) is an important area where ML models are used for subgrid modelling: making predictions of processes occ… (voir plus)urring at scales too small to be resolved by standard solution methods(Brasseur & Jacob, 2017). These models are expected to make accurate predictions, even on out-of-distribution (OOD) data, and are additionally expected to respect important physical constraints of the ground truth model (Kashinath et al., 2021). While many specialized ML PDE solvers have been developed, the particular requirements of CWM models have not been addressed so far. The goal of this work is to address them. We propose and develop a novel architecture, which matches or exceeds the performance of standard ML models, and which demonstrably succeeds in OOD generalization. The architecture is based on expert knowledge of the structure of PDE solution operators, which permits the model to also obey important physical constraints
2000-01-01
(publié)
www.semanticscholar.org