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)

AI for health: from prediction to prescription (dans la session "Life Sciences")

Assisting sampling of equilibrium physical states with generative models (dans la session "Material and Quantum Physics")

Building new brains for Adaptive Optics on giant optical telescopes. (dans la session "Astrophysics")

Designing Molecular RNA Switches with Restricted Boltzmann Machines (dans la session "Contributed Talks")

Empowering neursocience with AI (dans la session "Neuroscience")

Exploring language in the brain using Large Language Models (dans la session "Neuroscience")

Galaxy detection with deep learning in radio-astronomical datasets (dans la session "Astrophysics")

Incremental Neural Data Assimilation (dans la session "Contributed Talks")

Introduction to deep learning (dans la session "Machine Learning for Science School")

Large-scale auto-formalization of mathematical theories: why, how, and why now? (dans la session "Contributed Talks")

Learning with non-tabular data (dans la session "Machine Learning for Science School")

Machine Learning for Quantum Simulation (dans la session "Material and Quantum Physics")

Multi-modal learning for single-cell multi-omics data integration (dans la session "Life Sciences")

Natural Language Inference for clinical trials (dans la session "Life Sciences")

Optimising geometric deep learning methods for particle detection challenges in high energy physics experiments. (dans la session "Contributed Talks")

Quantum physics for machine learning (dans la session "Physics for Machine Learning")

Radar imaging for earth observation and climate science and the key contribution of machine learning (dans la session "Climate Sciences")

Scattering Spectra models for Physics (dans la session "Contributed Talks")

Some AI challenges in astrophysical imaging (dans la session "Astrophysics")

Statistical learning and model validation (dans la session "Machine Learning for Science School")

TBC (dans la session "Climate Sciences")

The quantum many-body problem and properties of materials: how to profit from machine learning? (dans la session "Material and Quantum Physics")

The scikit-learn API (dans la session "Machine Learning for Science School")

Understanding uncertainty in machine learning with tractable models (dans la session "Physics for Machine Learning")

Using machine learning to parameterize unresolved processes in climate models: a few thoughts on the example of gravity waves (dans la session "Climate Sciences")

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Sacl-AI 4 Science Workshop