DeepFDM, a differentiable finite-difference solver that learns PDE coefficients, achieves 10 to 40 times lower error than FNO, U-Net and ResNet on five scalar time-dependent PDEs in one to three dimensions.
Climode: Climate and weather forecasting with physics-informed neural odes
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Numerical PDE solvers outperform neural PDE solvers
DeepFDM, a differentiable finite-difference solver that learns PDE coefficients, achieves 10 to 40 times lower error than FNO, U-Net and ResNet on five scalar time-dependent PDEs in one to three dimensions.