NVRNet uses pretrained simulation-based U-Nets with attention and parameter-efficient adapters, followed by a transformer estimator, to reconstruct clean Ramsey waveforms and infer hyperfine parameters from minimal-sweep experimental data, achieving 0.44-0.67x noise reduction and 0.10-0.19 FFT error
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4 Pith papers cite this work. Polarity classification is still indexing.
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The Weak Penalty Neural ODE uses a weak form loss to filter noise and learn stable chaotic dynamics from noisy observations.
Neural-network quantum states locate stable bright solitons in a harmonically trapped repulsive 1D BEC that recur after one trap period.