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By explicitly encoding Green's function theory into a neural architecture, DGNet learns spatiotemporal PDEs from just tens of training trajectories, outperforming existing methods.
LLMs learn faster and perform better in decision-making tasks when rewarded for being uncertain, not just for succeeding.
