Présidents de session
COLOURS School: Opening
- Samuel Farrens (CosmoStat, CEA Paris-Saclay)
COLOURS School: Cosmology I
- Calum Murray (CosmoStat, CEA Paris-Saclay)
COLOURS School: Cosmology II
- Natalia Porqueres (CosmoStat, CEA Paris-Saclay)
COLOURS School: Data Science I
- Samuel Farrens (CosmoStat, CEA Paris-Saclay)
COLOURS School: Communication
- Melissa Ann Thomas (CentraleSupélec)
COLOURS School: Cosmology III
- Stefano Camera (University of Turin)
COLOURS School: Cosmology IV
- Giovanni Aricò (INFN Bologna)
COLOURS School: Cosmology V
- Andrina Nicola (University of Bonn)
COLOURS School: Transferable Skills
- Il n'a pas de président de session pour ce bloc
COLOURS School: Data Science II - Group A
- Il n'a pas de président de session pour ce bloc
COLOURS School: Data Science II - Group B
- Il n'a pas de président de session pour ce bloc
COLOURS School: Pasqal Site Visit - Group B
- Il n'a pas de président de session pour ce bloc
COLOURS School: Pasqal Site Visit - Group A
- Il n'a pas de président de session pour ce bloc
A hands-on guide to making robust and professional software
A hands-on guide to making robust and professional software
Numerical simulations currently provide our most accurate predictions for structure formation in the Universe, in a wide range of scales and redshifts.
We will overview cosmological N-body simulations, discussing common assumptions, approximations and regime of applicability.
Furthermore, we will introduce the main hydrodynamical schemes, and review the sub-grid prescriptions used to model...
Numerical simulations currently provide our most accurate predictions for structure formation in the Universe, in a wide range of scales and redshifts.
We will overview cosmological N-body simulations, discussing common assumptions, approximations and regime of applicability.
Furthermore, we will introduce the main hydrodynamical schemes, and review the sub-grid prescriptions used to model...
In a world facing increasingly complex global challenges, creativity and adaptability are no longer optional—they are essential. This session explores how Artificial Intelligence (AI) can support and enhance human creativity to foster innovative, context-aware solutions across diverse fields—from sustainability to social transformation, and from theoretical foundations to the arts. Drawing on...
Empirical risk minimization learning paradigm works under the assumption that training and test data are identically distributed. However, this hypothesis is seldom met in practice, due to several factors including changes in the underlying physical process generating the data, data acquisition conditions or sensors drifts. This problem is known as distributional shift between the reference...
Panel members:
- Ben Hoyle (Zeiss, DE)
- Denise Lanzieri (Sony CSL, IT)
- Fred Ngolè Mboula (CEA LETI, FR)
- Prina Patel (Mastercard, UK)
