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 (in session "Life Sciences")

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

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

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

Empowering neursocience with AI (in session "Neuroscience")

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

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

Incremental Neural Data Assimilation (in session "Contributed Talks")

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

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

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

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

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

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

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

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

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

Scattering Spectra models for Physics (in session "Contributed Talks")

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

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

TBC (in session "Climate Sciences")

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

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

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

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

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Sacl-AI 4 Science Workshop