Elishai Ezra Tsur

Collocation geometry creates structural blind spots in physics-informed neural networks

Physics-informed neural networks (PINNs) minimize empirical residuals of governing equations, but a small sampled residual need not certify the structural properties of the underlying partial differential equation (PDE). We examine this issue from a discrete least-squares viewpoint using sampled-residual observability...