IN2P3 School of Statistics 2026

Jun 1, 2026, 9:00 AM → Jun 5, 2026, 11:15 PM Europe/Paris

Centre de Vacances CAES du CNRS Paul Langevin, Aussois, Savoie

The tenth edition of the IN2P3 School Of Statistics will be held from Monday, June 1 to Friday, June 5 2026 in Aussois (Savoie).

The school is intended for PhD students, post-doctoral researchers, and senior scientists and engineers who wish to strengthen their expertise or explore new methods in statistical analysis and machine learning as applied to subatomic physics, astroparticle physics, and cosmology.

 

The school combines lectures and hands-on sessions with (online) Jupyter notebooks. All lectures will be given in English.

The School Of Statistics is supported by CNRS/IN2P3.

Programme

Courses and hands-on sessions (get ready !)

• Basic concepts of statistics: Romain Madar (LPCA, Clermont-Ferrand)
• Classical interval estimation, limits, systematics and beyond: Lydia Brenner (CERN) and Nicolas Berger (LAPP, Annecy)
• Introduction to machine learning: Vincent Barra (UCA, Clermont-Ferrand) and Yann Coadou (CPPM, Marseille)
• Anomaly detection: Emille Ishida (LPCA, Clermont-Ferrand)
• Bayesian statistics and sampling techniques: Florian Ruppin (Université Lyon 1 - IP2I) and Cyrille Doux (LPSC, Grenoble)
• Introduction to deep learning: Florian Ruppin (Université Lyon 1 - IP2I)
• Simulation based inference: Cyrille Doux (LPSC, Grenoble)

The school will also feature a discussion on the ethical/environmental aspects of AI (Steven Schramm, Unige), a mini-hackathon and a presentation about foundation models (François Lanusse, CEA Saclay).

Registration fees

• CNRS employees (ie directly paid by CNRS): 0€
• PhD students in a IN2P3 lab: 300€
• All other participants: 900€

Full board (housing, meals, breaks) is included in your fee from May 31 (dinner) to June 5 (lunch).

Financial Support

The IN2P3 School of Statistics 2026 acknowledges support from CNRS, Université Grenoble-Alpes (UGA), the Multidisciplinary Institute in Artificial intelligence (MIAI) at UGA and France 2030.

Organizing Committee

Johan Bregeon (LPSC, Grenoble), Yann Coadou (CPPM, Marseille), Sabine Crépé-Renaudin (LPSC, Grenoble), Cyrille Doux (LPSC, Grenoble, chair), Giulio Dujany (IPHC, Strasbourg), Leïla Haegel (IP2I, Lyon), Emille Ishida (LPCA, Clermont-Ferrand), Romain Madar (LPCA, Clermont-Ferrand), Guillaume Mention (CEA/IRFU, Saclay), David Rousseau (IJCLab, Orsay)

Administrative Support

Françoise Petiot / Cécile Martin / Cécile Vannier (LPSC, Grenoble)

Mon, June 1

1 Welcome

Speaker: Cyrille Doux (LPSC)

12:00 PM Lunch

2 Basic concepts of statistics - Part I

Speaker: Romain Madar (Laboratoire de Physique Corpusculaire de Clermont-Ferrand (LPC))

3:30 PM Break

3 Basic concepts of statistics - Part II

Speaker: Romain Madar (Laboratoire de Physique Corpusculaire de Clermont-Ferrand (LPC))

Tue, June 2

4 Classical interval estimation, limits, systematics and beyond - Part I

Speakers: Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam), Nicolas Berger (LAPP)

10:30 AM Break

5 Classical interval estimation, limits, systematics and beyond - Part II

Speakers: Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam), Nicolas Berger (LAPP)

12:30 PM Lunch

6 Hands-on: statistics

Speakers: Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam), Nicolas Berger (LAPP)

3:30 PM Break

7 Hands-on: statistics

Speakers: Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam), Nicolas Berger (LAPP)

8 Pizza discussion: environmental and ethical impacts of AI and good practices

Speaker: Steven Schramm (University of Geneva)

Wed, June 3

9 Introduction to machine learning

Speaker: Vincent Barra (UCA)

10:30 AM Break

10 Hands-on: Introduction to machine learning tools

Speaker: Yann Coadou (CPPM, Aix-Marseille Université, CNRS/IN2P3 (FR))

12:30 PM Lunch

11 Anomaly detection

Speaker: Dr Emille Ishida (CNRS/LPC-Clermont)

3:30 PM Break

12 Hackathon

Thu, June 4

13 Bayesian inference

Speakers: Cyrille Doux (LPSC), Florian Ruppin (IP2I Lyon)

10:30 AM Break

14 Hands-on: Sampling techniques

Speakers: Cyrille Doux (LPSC), Florian Ruppin (IP2I Lyon)

12:30 PM Lunch

15 Introduction to deep learning

Speaker: Florian Ruppin (Université Lyon 1 - IP2I)

3:30 PM Break

16 Hands-on: deep learning

Speaker: Florian Ruppin (Université Lyon 1 - IP2I)

8:00 PM Social dinner

Fri, June 5

17 Simulation based inference

Speaker: Cyrille Doux (LPSC)

10:30 AM Break

18 Foundation models

Speaker: Francois Lanusse ({CNRS}UMR7158)

19 Farewell

Speaker: Yann Coadou (CPPM, Aix-Marseille Université, CNRS/IN2P3 (FR))

12:30 PM Lunch

1:30 PM Departure