arxiv
PublishedJuly 27, 2026 at 4:00 AM
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Explainable quantum-compressed machine learning for complex fluid flows
Publisher summary· verbatim
arXiv:2607.21688v1 Announce Type: cross Abstract: Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep surrogates match high-fidelity simulations only through massive parame
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Originally published on arxiv ↗