A self-refining training loop, where a neural network samples molecular conformations from its own predicted energy and trains on them, reduces the need for large labeled DFT datasets in amortized density functional theory.
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Self-Refining Training for Amortized Density Functional Theory
A self-refining training loop, where a neural network samples molecular conformations from its own predicted energy and trains on them, reduces the need for large labeled DFT datasets in amortized density functional theory.