Operator Learning with Neural Fields: Tackling PDEs on General Geometries. - Louis Serrano; Lise Le Boudec; Armand Kassaï Koupaï; Thomas X. Wang; Yuan Yin; Jean-Noël Vittaut; Patrick Gallinari (NeurIPS, 2023)

INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations. - Louis Serrano; Léon Migus; Yuan Yin; Jocelyn Ahmed Mazari; Patrick Gallinari (CoRR, 2023)

AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields. - Louis Serrano; Thomas X. Wang; Etienne Le Naour; Jean-Noël Vittaut; Patrick Gallinari (NeurIPS, 2024)

ACCO: Accumulate while you Communicate, Hiding Communications in Distributed LLM Training. - Adel Nabli; Louis Fournier; Pierre Erbacher; Louis Serrano; Eugene Belilovsky; Edouard Oyallon (CoRR, 2024)

Zebra: In-Context and Generative Pretraining for Solving Parametric PDEs. - Louis Serrano; Armand Kassaï Koupaï; Thomas X. Wang; Pierre Erbacher; Patrick Gallinari (CoRR, 2024)

Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods. - Lise Le Boudec; Emmanuel de Bézenac; Louis Serrano; Ramon Daniel Regueiro-Espino; Yuan Yin; Patrick Gallinari (CoRR, 2024)

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations. - Etienne Le Naour; Louis Serrano; Léon Migus; Yuan Yin; Ghislain Agoua; Nicolas Baskiotis; Patrick Gallinari; Vincent Guigue (Trans. Mach. Learn. Res., 2024)

Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods. - Lise Le Boudec; Emmanuel de Bézenac; Louis Serrano; Ramon Daniel Regueiro-Espino; Yuan Yin; Patrick Gallinari (ICLR, 2025)

ENMA: Tokenwise Autoregression for Generative Neural PDE Operators. - Armand Kassaï Koupaï; Lise Le Boudec; Louis Serrano; Patrick Gallinari (CoRR, 2025)

JAFAR: Jack up Any Feature at Any Resolution. - Paul Couairon; Loïck Chambon; Louis Serrano; Jean-Emmanuel Haugeard; Matthieu Cord; Nicolas Thome (CoRR, 2025)