Author

Jorge da Silva Goncalves

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#artificial intelligence Preprint Sep 2026

Wavelet Flow Matching for Time Series

Synthetic time series are increasingly used for data augmentation, privacy-preserving data sharing, and downstream model development, yet faithfully reproducing both multi-scale temporal structure and cross-channel dependencies remains challenging. We study multivariate time-series generation through flow matching in t...

Lucas Poinsignon, Jorge da Silva Goncalves, Samuel Ruipérez-Campillo et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Cyclostationary Phase Conditioning for Medical Time Series Diffusion

Across modalities, the results show that explicitly encoding measurable cyclic structure improves physiological time-series restoration and proposes antithetic coupling of reverse trajectories to reduce sampling variance while achieving comparable performance with fivefold fewer network evaluations.

Samuel Ruipérez-Campillo, Michele Copetti, Jorge da Silva Goncalves et al. · 1 citation