PDEInvBench supplies a new benchmark dataset for PDE inverse problems and shows that two-stage supervised-plus-test-time training, PDE derivative inputs, and diverse initial conditions improve neural network accuracy on parameter recovery.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems
PDEInvBench supplies a new benchmark dataset for PDE inverse problems and shows that two-stage supervised-plus-test-time training, PDE derivative inputs, and diverse initial conditions improve neural network accuracy on parameter recovery.