SGD and stochastic gradient flow are proven to drive the empirical PINN loss for the Poisson equation to zero exponentially in expectation, for sufficiently wide two-layer networks.
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Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks for the Poisson Equation
SGD and stochastic gradient flow are proven to drive the empirical PINN loss for the Poisson equation to zero exponentially in expectation, for sufficiently wide two-layer networks.