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20242026
most citedPriPHiT: Privacy-Preserving Hierarchical Training of Deep Neural Networks

1 citations · 1 across the 7 of their papers we have counts for

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cs.LG2026

PING: physics informed graph neural network for advection-diffusion processes with applications to solar power forecasting

Jelena Simeunović, Baptiste Schubnel, Pierre-Jean Alet +2

Advection-diffusion plays an essential role in transport phenomena such as atmospheric and cloud dynamics. Improved forecasting of cloud motion, in turn, enhances solar power produ…

cs.LG2026

Geodesics of Dynamic Graphs for Regime Change Detection

William Cappelletti, Étienne Voutaz, Pascal Frossard

Traditional change point detection in dynamic networks assumes abrupt transitions between stationary states, overlooking scenarios of continuous evolution which arise in most real-…