2 citations · 4 across the 2 of their papers we have counts for
3 papers · 1 filter
INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations
Louis Serrano, Leon Migus, Yuan Yin +2
For numerical design, the development of efficient and accurate surrogate models is paramount. They allow us to approximate complex physical phenomena, thereby reducing the computa…
Stability of implicit neural networks for long-term forecasting in dynamical systems
Leon Migus, Julien Salomon, Patrick Gallinari
Forecasting physical signals in long time range is among the most challenging tasks in Partial Differential Equations (PDEs) research. To circumvent limitations of traditional solv…
Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
Etienne Le Naour, Louis Serrano, Léon Migus +5
We introduce a novel modeling approach for time series imputation and forecasting, tailored to address the challenges often encountered in real-world data, such as irregular sample…