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October 16, 2025Open Access

Path Gradients after Flow Matching

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A hybrid approach using path gradients can increase sampling efficiency by up to threefold for molecular systems.
Experiments indicate that this method retains the learned structure of continuous normalizing flows during fine-tuning.
Using path gradients allows for optimization without requiring additional sampling or increased computational resources.
Flow matching plays a crucial role in speeding up continuous normalizing flows for complex molecular systems.

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Investigation reveals that path gradients improve sampling efficiency in molecular systems, suggesting enhancement of training methods.

Vaitl et al. (2025) studied this question.

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