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Overparameterization doesn't just add parameters; it warps the loss landscape geometry itself, making well-conditioned minima easier to find.
Deep learning finally cracks the DFT accuracy-efficiency trade-off, enabling highly accurate quantum chemistry calculations at semi-local DFT cost.
