#### TUTORIALS

**Ali Mohammad-Djafari (CNRS, France) -**Bayesian and Machine Learning Methods for Inverse Problem**Kevin H. Knuth**(University at Albany, USA) - Why Mathematics Works and Why Physics is Mathematical**John Skilling**(University of Cambridge, UK) - Foundations**Frank Nielsen**(Sony CSL, Japan) - Introduction to Information Geometry**Fréderic Barbaresco**(THALES, France) - Symplectic Theory of Heat and Information based on Souriau Lie Groups Thermodynamics, Coquinot Thermodynamic Dissipative Bracket and Sabourin Transverse Poisson Structures: Applications to Lindblad Equation**Ariel Caticha**(University at Albany, USA) - Entropic Dynamics and Quantum Measurement

#### INVITED TALKS

**Anna Simoni**(ENSAE, France) – Bayesian Exponentially Tilted Empirical Likelihood to Endogeneity Testing**Antoine Bourget**(CEA and ENS Paris, France) - The Geometry of Quivers**Bobak Toussi Kiani**(MIT, USA) - Quantum algorithms for group convolution, cross-correlation, and equivariant transformations**Emtiyaz Khan (**RIKEN, Japan) - The Bayesian Learning Rule**Fabrizia Guglielmetti**(ALMA Regional Center Scientist at European Southern Observatory, Germany) – Bayesian and Machine Learning methods in the Big Data era for astronomical imaging**Livia Partay**(University of Warwick, UK) - Nested sampling for materials**Lorenzo Valzania**(LKB: Sorbonne University - ENS - Collège de France, France) - Imaging behind scattering layers**Pierre-Henri Wuillemin**(Laboratoire d'Informatique de Paris, France) - Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks**Torsten Ensslin**(MPA , Germany) - Theoretical Modeling of Communication Dynamics**Will Handley**(University of Cambridge, UK) - Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning**Piotr Graczyk**(Angers, France) - Graphical Gaussian models associated to a homogeneous graph with permutation symmetries**Olivier Rioul**(Telecom ParisTech) - What is Randomness? The Interplay between Alpha Entropies, Total Variation and Guessing

#### INVITED SPEAKER ON PROBABILITY HISTORY

**Borel and the emergence of probability on the mathematical scene in France**

**Laurent Mazliak** (Sorbonne Université, LPSM)

*The inauguration of the Institut Henri Poincaré in 1928 marked an important date with the institution for the first time of a permanent teaching and research in the field of probability in France at the highest level. The mathematician Emile Borel was the main architect of this evolution, after having himself invested heavily in this discipline from 1905 onwards, and because he was aware of the worrying delay of the French mathematical community in these subjects compared to other countries such as Germany, Great Britain or Italy. My presentation will recall how Borel's trajectory led him to become interested in the mathematics of chance and how he used his political investment in the 1920s to push forward his project of large-scale dissemination of probability in the inter-war period. I will also describe how the early years of the IHP with the action of Fréchet and Darmois allowed a small community of specialists to emerge in France, which played an important role in the evolution of the discipline in the second half of the twentieth century. *