Hi I'm Armand! Some stuff about me :)
I am currectly a PhD student at Sorbonne Université at ISIR (MLIA Team) under the supervision of Patrick Gallinari and Jean-Noël Vittaut, where my research focus is deep learning for solving parametric PDEs. I am particularly interested in out-of-distribution generelization, generative modeling and foundation models for science.
Recent News
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(Oct 2024) I participated in the GenAI Autumn School at Saclay, to learn more about generative modeling and its application in text, vision, speech, IoT, etc.
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(Oct 2024) New preprint Zebra: In-Context and Generative Pretraining for Solving Parametric PDEs available on Arxiv and submitted for ICLR 2025.
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(Sept 2024) Our paper GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning has been accepted at NeurIPS 2024.
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(July 2024) I participated to the Climate AI Summer School , where I learned a lot of applications of ML for climate purposes in fields such as energy and agriculture.
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(March 2024) Our paper Learn to adapt parametric solvers under incomplete physics has been accepted at the AI4DiffEqtnsInSci Workshop at ICLR 2024.
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(Sept 2023) Our paper Operator Learning with Neural Fields: Tackling PDEs on General Geometries has been accepted at the AI4DiffEqtnsInSci Workshop at ICLR 2024.
Selected Publications
See Google Scholar for a complete list of my publications.
Louis Serrano, Armand Kassaï Koupaï, Thomas X Wang, Pierre Erbacher, Patrick Gallinari
Armand Kassaï Koupaï, Jorge Misfut Benet, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari
Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari