INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations

no code implementations • 25 Jul 2023 • Louis Serrano, Leon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari

For numerical design, the development of efficient and accurate surrogate models is paramount.

Operator Learning with Neural Fields: Tackling PDEs on General Geometries

1 code implementation • NeurIPS 2023 • Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari

Machine learning approaches for solving partial differential equations require learning mappings between function spaces.

Operator learning Spatio-Temporal Forecasting

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations

1 code implementation • 9 Jun 2023 • Etienne Le Naour, Louis Serrano, Léon Migus, Yuan Yin, Ghislain Agoua, Nicolas Baskiotis, Patrick Gallinari, Vincent Guigue

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 samples, missing data, or unaligned measurements from multiple sensors.

Imputation Meta-Learning +1