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A novel neural network framework achieves high accuracy in solving PDEs on unbounded domains by intelligently decomposing spatial regions into specialized subnetworks.
Randomly initialized neural nets can solve high-dimensional integro-differential equations like neutron transport faster and more stably than both physics-informed neural networks and traditional deterministic methods.
