Author

Thibault Pautrel

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Preprint Sep 2026

Global universality of the expected number of zeros of non-analytic random signals

We study the asymptotics as $n$ goes to infinity of $\mathbb E\left[\mathcal{N}(S_n,[0,2\pi])\right]$, the expected number of zeros in $[0, 2\pi]$ of a random periodic signal $S_n$ of the form \[ S_n(t)=\sum_{k=1}^{n}a_k f(kt), \] where $f$ is a non-analytic $2\pi-$periodic function and the coefficients $(a_k)$ are i.i...

Jurgen Angst, Thibault Pautrel, Guillaume Poly · 0 citations

#machine learning Preprint Sep 2026

Personalised federated learning for Riemannian and Euclidean EEG decoding

It is observed that personalised SPDNet reaches higher accuracy than both standard FL and centralised training, while converging in fewer rounds and communicating fewer parameters than standard FL.

Thibault Pautrel, Florent Bouchard, Ammar Mian et al. · 0 citations

#machine learning Apr 2026

FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet

Simulations on EEG motor imagery benchmarks show that FedSPDnet outperforms federated EEGnet in F1 score and robustness to federation and partial participation, while using fewer parameters per communication round.

Thibault Pautrel, Florent Bouchard, Ammar Mian et al. · arXiv.org · 2 citations