Name: Sacl-AI 4 Science Workshop
Start: 2024-07-08T08:00:00+02:00
End: 2024-07-12T16:45:00+02:00
Location: BÂTIMENT D’ENSEIGNEMENT MUTUALISÉ (BEM)

Sacl-AI 4 Science Workshop

de lundi 8 juillet 2024 (08:00) à vendredi 12 juillet 2024 (16:45)

lundi 8 juillet 2024
09:30 Introduction to ML - O. Colliot
Introduction to ML - O. Colliot
09:30 - 12:30
Contributions

09:30 Statistical learning and model validation - Olivier Colliot
12:30 Lunch break
Lunch break
12:30 - 14:00
14:00 The scikit-learn API - G. Lemaitre
The scikit-learn API - G. Lemaitre
14:00 - 17:00
Contributions

14:00 The scikit-learn API - Guillaume Lemaitre
mardi 9 juillet 2024
09:30 Learning with non-tabular data - T. Moreau
Learning with non-tabular data - T. Moreau
09:30 - 12:30
Contributions

09:30 Learning with non-tabular data - Thomas Moreau (Inria)
12:30 Lunch break
Lunch break
12:30 - 14:00
14:00 Intro to deep learning - R. Menegaux
Intro to deep learning - R. Menegaux
14:00 - 17:00
Contributions

14:00 Introduction to deep learning - Romain Ménégaux
mercredi 10 juillet 2024
09:30
09:30 - 11:00
Contributions

09:30 Machine Learning for Quantum Simulation - Filippo Vicentini (École Polytechnique - CPHT)

10:15 The quantum many-body problem and properties of materials: how to profit from machine learning? - Lucia Reining
11:00 Coffee Break
Coffee Break
11:00 - 11:30
11:30 Material & Quantum Physics (II)
Material & Quantum Physics (II)
11:30 - 12:15
Contributions

11:30 Assisting sampling of equilibrium physical states with generative models - Marylou Gabrié (École Polytechnique)
12:30 Lunch
Lunch
12:30 - 14:00
14:00 Physics for Machine Learning
Physics for Machine Learning
14:00 - 15:30
Contributions

14:00 Quantum physics for machine learning - Danijela Markovic (CNRS Thales)

14:45 Understanding uncertainty in machine learning with tractable models - Bruno Loureiro (ENS Ulm)
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00
16:00 - 17:00
Contributions

16:00 Designing Molecular RNA Switches with Restricted Boltzmann Machines - Jorge FERNANDEZ-DE-COSSIO-DIAZ (ENS Paris)

16:20 Optimising geometric deep learning methods for particle detection challenges in high energy physics experiments. - Matthieu Melennec

16:40 Scattering Spectra models for Physics - Rudy Morel (Flatiron Institute)
jeudi 11 juillet 2024
09:30 Climate Science (I)
Climate Science (I)
09:30 - 11:00
Contributions

09:30 Using machine learning to parameterize unresolved processes in climate models: a few thoughts on the example of gravity waves - Riwal Plougonven

10:15 Radar imaging for earth observation and climate science and the key contribution of machine learning - Florence Tupin (Telecom Paris)
11:00 Coffee Break
Coffee Break
11:00 - 11:30
11:30 Climate Science (II)
Climate Science (II)
11:30 - 12:15
Contributions

11:30 TBC - Julien Le Sommer
12:15
12:15 - 12:35
Contributions

12:15 Incremental Neural Data Assimilation - Matthieu Blanke (Inria Paris, DI ENS)
12:35 Lunch
Lunch
12:35 - 14:00
14:00
14:00 - 15:30
Contributions

14:00 Some AI challenges in astrophysical imaging - Jerome Bobin

14:45 Galaxy detection with deep learning in radio-astronomical datasets - David Cornu (Observatoire de Paris)
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00
16:00 - 16:45
Contributions

16:00 Building new brains for Adaptive Optics on giant optical telescopes. - Damien Gratadour (Observatoire de Paris)
17:00 Poster Session
Poster Session
17:00 - 18:30
vendredi 12 juillet 2024
10:15
10:15 - 11:00
Contributions

10:15 Empowering neursocience with AI - Bertrand Thirion (Inria)
11:00 Coffee Break
Coffee Break
11:00 - 11:30
11:30
11:30 - 12:15
Contributions

11:30 Exploring language in the brain using Large Language Models - Christophe Pallier (EMR CNRS 9003 & INSERM-CEA Cognitive Neuroimaging Lab U992)
12:15
12:15 - 12:35
Contributions

12:15 Large-scale auto-formalization of mathematical theories: why, how, and why now? - Fabian Gloeckle (Ecole des Ponts ParisTech)
12:35 Lunch
Lunch
12:35 - 14:00
14:00
14:00 - 15:30
Contributions

14:00 Multi-modal learning for single-cell multi-omics data integration - Laura Cantini (Institut Pasteur)

14:45 AI for health: from prediction to prescription - Judith Abecassis (Inria)
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00
16:00 - 16:45
Contributions

16:00 Natural Language Inference for clinical trials - Nona Naderi

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