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

from Monday, July 8, 2024 (8:00 AM) to Friday, July 12, 2024 (4:45 PM)

Monday, July 8, 2024
9:30 AM Machine Learning for Science School: Introduction to ML - O. Colliot
Introduction to ML - O. Colliot
9:30 AM - 12:30 PM
Contributions

9:30 AM Statistical learning and model validation - Olivier Colliot
12:30 PM Lunch break
Lunch break
12:30 PM - 2:00 PM
2:00 PM Machine Learning for Science School: The scikit-learn API - G. Lemaitre
The scikit-learn API - G. Lemaitre
2:00 PM - 5:00 PM
Contributions

2:00 PM The scikit-learn API - Guillaume Lemaitre
Tuesday, July 9, 2024
9:30 AM Machine Learning for Science School: Learning with non-tabular data - T. Moreau
Learning with non-tabular data - T. Moreau
9:30 AM - 12:30 PM
Contributions

9:30 AM Learning with non-tabular data - Thomas Moreau (Inria)
12:30 PM Lunch break
Lunch break
12:30 PM - 2:00 PM
2:00 PM Machine Learning for Science School: Intro to deep learning - R. Menegaux
Intro to deep learning - R. Menegaux
2:00 PM - 5:00 PM
Contributions

2:00 PM Introduction to deep learning - Romain Ménégaux
Wednesday, July 10, 2024
9:30 AM Material and Quantum Physics
9:30 AM - 11:00 AM
Contributions

9:30 AM Machine Learning for Quantum Simulation - Filippo Vicentini (École Polytechnique - CPHT)

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

11:30 AM Assisting sampling of equilibrium physical states with generative models - Marylou Gabrié (École Polytechnique)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM Physics for Machine Learning: Physics for Machine Learning
Physics for Machine Learning
2:00 PM - 3:30 PM
Contributions

2:00 PM Quantum physics for machine learning - Danijela Markovic (CNRS Thales)

2:45 PM Understanding uncertainty in machine learning with tractable models - Bruno Loureiro (ENS Ulm)
3:30 PM Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM Contributed Talks
4:00 PM - 5:00 PM
Contributions

4:00 PM Designing Molecular RNA Switches with Restricted Boltzmann Machines - Jorge FERNANDEZ-DE-COSSIO-DIAZ (ENS Paris)

4:20 PM Optimising geometric deep learning methods for particle detection challenges in high energy physics experiments. - Matthieu Melennec

4:40 PM Scattering Spectra models for Physics - Rudy Morel (Flatiron Institute)
Thursday, July 11, 2024
9:30 AM Climate Sciences: Climate Science (I)
Climate Science (I)
9:30 AM - 11:00 AM
Contributions

9:30 AM Using machine learning to parameterize unresolved processes in climate models: a few thoughts on the example of gravity waves - Riwal Plougonven

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

11:30 AM TBC - Julien Le Sommer
12:15 PM Contributed Talks
12:15 PM - 12:35 PM
Contributions

12:15 PM Incremental Neural Data Assimilation - Matthieu Blanke (Inria Paris, DI ENS)
12:35 PM Lunch
Lunch
12:35 PM - 2:00 PM
2:00 PM Astrophysics
2:00 PM - 3:30 PM
Contributions

2:00 PM Some AI challenges in astrophysical imaging - Jerome Bobin

2:45 PM Galaxy detection with deep learning in radio-astronomical datasets - David Cornu (Observatoire de Paris)
3:30 PM Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM Astrophysics
4:00 PM - 4:45 PM
Contributions

4:00 PM Building new brains for Adaptive Optics on giant optical telescopes. - Damien Gratadour (Observatoire de Paris)
5:00 PM Poster Session
Poster Session
5:00 PM - 6:30 PM
Friday, July 12, 2024
10:15 AM Neuroscience
10:15 AM - 11:00 AM
Contributions

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

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

12:15 PM Large-scale auto-formalization of mathematical theories: why, how, and why now? - Fabian Gloeckle (Ecole des Ponts ParisTech)
12:35 PM Lunch
Lunch
12:35 PM - 2:00 PM
2:00 PM Life Sciences
2:00 PM - 3:30 PM
Contributions

2:00 PM Multi-modal learning for single-cell multi-omics data integration - Laura Cantini (Institut Pasteur)

2:45 PM AI for health: from prediction to prescription - Judith Abecassis (Inria)
3:30 PM Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM Life Sciences
4:00 PM - 4:45 PM
Contributions

4:00 PM Natural Language Inference for clinical trials - Nona Naderi

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