IA@IRAP 2025 Day

Liste des Contributions

4. Welcome

15/10/2025 09:00

5. AI for SDU at OMP and the region

Etienne Gondet (OMP)

15/10/2025 09:05

2. Comment ça marche Chat GPT ? une introduction à l'Intelligence Artificielle

Jonathan Sprauel (IRT Saint-Exupéry)

15/10/2025 09:20

Tout ce que vous avez toujours voulu savoir sur l'Intelligence Artificielle, depuis l'optimisation et les modèles d'analyse d'image jusqu'au grands modèles de langage : quelles sont les différentes technologies et comment elles marchent, est-ce qu'on peut avoir confiance dans l'IA, quelles techniques d'IA je peux utiliser aujourd'hui dans mon métier, que font les chercheurs en IA, quels sont...

19. AI or not AI ? Overview of methods developed at SISU

Hervé Carfantan

15/10/2025 10:30

6. Physics models in Unrolling algorithms applied to Coded-Aperture Snapshot Spectral Imagers

Léo Paillet

15/10/2025 11:10

Léo Paillet, Hervé Carfantan, Simon Lacroix, Antoine Monmayrant

We made a CASSI (Coded Aperture Snapshot Spectral Imager) optical simulator which allows to consider a realistic optical model. The model is then used to map input positions to output positions in order to adapt unrolling algorithms to realistic systems. Through this simulator and mapping function, we prove that the inverse...

7. What can we learn from the XMM source catalog ?

Simon Dupourqué (GAHEC)

15/10/2025 11:30

The 4XMM catalogue contains more than 20 years of X-ray observations. However, exploiting this data on the catalogue scale is not straightforward since most of the automatically extracted sources do not have a precise classification. Our aim is to use machine learning, specifically a variational autoencoder, to embed the sources in a latent space that is more suitable for exploring and...

8. Machine Learning-Led Classification of X-ray Sources Through Time-Domain Variability

Robbie Webbe (GAHEC)

15/10/2025 11:50

Unusual patterns of variability in X-ray sources can hold clues to the identities of hard to classify sources, and can be indicators of rare and exotic astrophysical phenomena like magnetar outbursts and Quasi-Periodic Eruptions in AGN. The ability to adequately identify interesting sources through their time-domain variability can often be difficult with the large volumes of data being...

9. Unsupervised classification of galaxy spectra up to z~1.2. Towards galaxy spectral evolution ?

Jihane Moultaka (GAHEC)

15/10/2025 12:10

I will present our results of spectral galaxy classifications from GAMA and VIPERS surveys in the nearby universe and up to z~1.2 using an unsupervised method called Fisher-EM. This method is particularly well-suited to high-dimensional parameter spaces as is the case of galaxy spectra. Our approach enables us to highlight classes of galaxy spectra that allow to refine the bimodal distribution...

3. Panorama des activités IA sur ARIEL

Orphée Faucoz (CNES)

15/10/2025 14:00

La mission ARIEL de l'ESA vise à analyser la composition chimique des atmosphères exoplanétaires grâce à la spectroscopie de transit. Cette présentation se concentrera sur l'utilisation du Machine Learning pour transformer et améliorer les données ARIEL, en s'appuyant notamment sur des Data Challenges dédiés et des approches innovantes. Nous présenterons comment l'apprentissage automatique est...

11. RMI Analyst

Olivier Gasnault (IRAP)

15/10/2025 14:35

We are developing a tool to classify images taken by ChemCam on Mars and rank their similarities.

12. Investigating the benefits of Deep Learning for particle pulse-shape discrimination in a space-borne silicon detector

Pierre Devoto (IRAP/CNRS)

15/10/2025 14:55

The SP@M (for Solar Particles @ Mars) instrument onboard M-MATISSE will measure Solar Energetic Particles (SEPs, protons and electrons) throughout the Martian magnetosphere and atmosphere. While most of today's on-board instruments discriminate particles using coincidence processing between 2 or more silicon detectors arranged as a telescope, SP@M proposes to use a single thick silicon...

10. SPARTAI — AI-based forecasting pipeline for energetic electrions in the Earth’s radiation belts

Rungployphan Kieokaew (IRAP et Inria Centre de Paris)

15/10/2025 15:15

Highly energetic electrons (at the MeV level) in the vicinity of the Earth’s radiation belts pose significant risks on satellites through single event effects and long-term radiation damage, in GEO, MEO, and LEO orbits. Accurate forecasting of electron fluxes in this environment is essential for risk mitigation and spacecraft operations. Over the past few decades, several physics-based models...

1. What do we know about the environmental impact of research computing (including AI, but not limited to it)?

Karin Dassas (CNRS, CESBIO)

15/10/2025 16:00

Cette présentation tentera d'apporter un éclairage sur l'impact environnemental que peuvent avoir les calculs faits à l'OMP, localement ou au sein de Calmip, Trex, ou les machines du GENCI. Elle abordera aussi l'impact de l'usage de l'IA générative pour aider à coder (IA4code), et la question des usages (IA4Green ?).

14. Coffee break

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15. Coffee break

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18. Contribution 1

Name

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13. contribution 8

Michel Blanc

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17. Lunch break (Buffet in Coriolis)