Program
| Topic 1: Foundations of probability, inference, information, entropy | |
| Topic 2: Bayesian Geometric-Informed, Physics-Informed & Thermodynamics-Informed Machine Learning | |
| Topic 3: Information theory, machine learning tools for inverse problems | |
| Topic 4: Bayesian and Maximum Entropy in real world applications | |
| Topic 5: Geometric Statistical Mechanics/Physics, Lie Groups Thermodynamics & Maximum Entropy Densities | |
| Topic 6: Quantum: Theory, Computation, Tomography and Applications |
Tutorials
| Tutorial 01 | Ali Mohammad-Djafari (Former Research Director of CNRS, France) | Bayesian and Machine Learning Methods for Inverse Problem | CHAIR: JOHN SKILLING |
| Tutorial 02 | Kevin H. Knuth (University at Albany, USA) | Why Mathematics Works and Why Physics is Mathematical | CHAIR: FREDERIC BARBARESCO |
| Tutorial 03 | John Skilling (University of Cambridge, UK) | Foundations | CHAIR: FREDERIC BARBARESCO |
| Tutorial 04 | Frank Nielsen (Sony CSL, Japan) | Introduction to Information Geometry | CHAIR: MARTINO TRASSINELLI |
| Tutorial 05 | 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 | CHAIR: VALERIE GIRARDIN |
| Tutorial 06 | Ariel Caticha (University at Albany, USA) | Entropic Dynamics and Quantum Measurement | CHAIRS: LIVIA BARTOK-PARTAY AND ALI DJAFARI |
| History of probability | Laurent Mazliak (Sorbonne Université, LPSM) | Borel and the emergence of probability on the mathematical scene in France |
Sessions
| Tuesday July 19 | |||
| SESSION 1 | Topic 3 | INFORMATION THEORY, INFORMATION GEOMETRY, AND MACHINE LEARNING | CHAIRS: JOHN SKILLING & ALI DJAFARI |
| Invited speaker 01 | 87 | Emtiyaz Khan | The Bayesian Learning Rule |
| Speaker | 71 | Fábio C. C. Meneghetti, Henrique K. Miyamoto and Sueli I. R. Costa | Information Properties of a Random Variable Decomposition through Lattices |
| Speaker | 80 | Andrija Kostić, Philipp Frank, Matteo Guardiani, Sebastian Hutschenreuter, Maximilian Kurthen, Reimar Leike and Torsten Enßlin | Bayesian Causal Inference with Information Field Theory |
| Speaker | 75 | Keiko Uohashi | A foliation of probability simplexes for transition of \alpha-parameters |
| SESSION 2 | Topic 4 | INFERENCE AND INFORMATION IN HUMAN ACTIVITIES | CHAIRS: KEVIN KNUTH & ALI DJAFARI |
| Invited speaker 02 | 23 | Torsten Ensslin | Reputation communication from an information perspective |
| Speaker | 86 | Christina Pawlowitsch | Strategic Manipulation in Bayesian Dialogues |
| Speaker | 32 | Andrew Charman | The Census and the Second Law: An Entropic Approach to Optimal Apportionment of Legislative Representatives |
| SESSION 3 | Topic 4 | IMAGING APPLICATIONS | CHAIRS: SACHA RANFTL & ALI DJAFARI |
| Invited speaker 03 | 52 | Lorenzo Valzania | Computational tools to control light through complex media |
| Speaker | 31 | Berlin Chen and Cyrus Mostajeran | Geometric learning of hidden Markov models via a method of moments algorithm |
| Speaker | 79 | Yannis Kalaidzidis | Revisiting multiple signal classification algorithm for super-resolution fluorescence microscopy in presence of non-uniform background |
| Speaker | 74 | Geoffroy Delamare and Ulisse Ferrari | Time-Dependent Maximum Entropy Model for Populations of Retinal Ganglion Cells |
| SESSION 4 | Topic 4 | BAYESIAN SIMULATION AND MODEL SELECTION | CHAIRS: JEAN-MICHEL GILLET & PIERRE-HENRI WUILLEMIN |
| Speaker | 38 | Florent Leclercq | Simulation-based inference of Bayesian hierarchical models while checking for model misspecification |
| Speaker | 70 | Orestis Loukas and Ho Ryun Chung | Model selection in the world of Maximum Entropy |
| Speaker | 67 | Łukasz Tychoniec, Fabrizia Guglielmetti, Philipp Arras, Torsten Ensslin and Eric Villard | Bayesian statistics approach to imaging of aperture synthesis data: RESOLVE meets ALMA |
| Speaker | 17 | Riko Kelter | The Full Bayesian Evidence Test: Theory and Applications in Bayesian response-adaptive clinical Trial Designs |
| Speaker | 19 | Philipp Joppich, Sebastian Dorn, Oliver De-Candido, Wolfgang Utschick and Jakob Knollmüller | Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders |
| SESSION 5 | Topic 4 | QUANTUM SYSTEMS | CHAIRS: UDO VON TOUSSAINT & MARIA TROCAN |
| Speaker | 27 | Philippe Jacquet | Is Quantum Tomography a difficult problem for Machine Learning? |
| Speaker | 72 | Mariela Portesi, Yanet Alvarez, Marcelo Losada and Gustavo Martin Bosyk | Reciprocity relations for quantum systems based on Fisher information |
| Speaker | 34 | François Verdeil, Yannick Deville and Alain Deville | A unitary quantum process tomography algorithm robust to systematic errors |
| Wednesday July 20 | |||
| SESSION 6 | Topic 4 | NESTED SAMPLING & APPLICATIONS | CHAIRS: JOHN SKILLING & MARTINO TRASSINELLI |
| Invited speaker 04 | 69 | Will Handley | Frontiers in Nested Sampling |
| Speaker | 46 | Johannes Buchner | Comparison of step samplers for nested sampling |
| Speaker | 84 | Nancy Paul | Precision Highly Charged Ion Spectroscopy and Atomic Form Factor Studies with Bayesian Analysis |
| Speaker | 65 | Aleksandr Petrosyan | SuperNest: accelerated nested sampling applied to astrophysics and cosmology |
| SESSION 7 | Topic 4 | APPLICATIONS IN SOLID STATE PHYSICS | CHAIRS: WILL HANDLEY & JEAN-MICHEL GILLET & MARTINO TRASSINELLI |
| Invited speaker 05 | 2 | Livia Partay | Nested sampling for materials |
| Speaker | 50 | Lune Maillard | Nested sampling for the exploration of potential energy surfaces |
| Speaker | 36 | Alessandra Del Masto | Handling uncertainties in the development of tight-binding potentials : application to Zr and Zr-H systems |
| SESSION 8 | Topic 2 | MACHINE LEARNING | CHAIRS: FABRIZIA GUGLILMETTI & FREDERIC BARBARESCO |
| Invited speaker 06 | 8 | Bobak Toussi Kiani | Quantum algorithms for group convolution, cross-correlation, and equivariant transformations |
| Speaker | 20 | Eliot Tron | Equivariant Neural Networks and Differential Invariants Theory for Solving Partial Differential Equations |
| Speaker | 21 | Pierre-Yves Lagrave | Adaptive Importance Sampling for Equivariant Group-Convolution Computation |
| Speaker | 49 | Sho Sonoda | Closed-form Expression of Parameter Distribution in Neural Network on Noncompact Symmetric Space |
| POSTER SESSION | (see below) | ||
| Thursday July 21 | |||
| SESSION 9 | Topic 1 | FOUNDATIONS | CHAIRS: ROMKE BONTEKOE & MARTINO TRASSINELLI |
| Invited speaker 07 | 35 | Olivier Rioul | What is Randomness? The Interplay between Alpha Entropies, Total Variation and Guessing |
| Speaker | 76 | Robert Niven | Fluid Densities Defined from Probability Density Functions, and New Families of Conservation Laws |
| Speaker | 14 | Margret Westerkamp, Igor Ovchinnikov, Philipp Frank and Torsten Enßlin | Analysis of dynamical field inference in a supersymmetric theory |
| Speaker | 83 | Roman Belavkin, Panos Pardalos and Jose Principe | Value of Information in the Binary Case and Confusion Matrix |
| SESSION 10 | Topic 1 | QUIVERS GEOMETRY AND NEURAL NETWORKS | CHAIRS: PHILIPPE JACQUET & FREDERIC BARBARESCO |
| Invited speaker 08 | 28 | Antoine Bourget | The Geometry of Quivers |
| Speaker | 55 | Marco Armenta | A Notion of Entropy for the study of Neural Network Training Dynamics using Quiver Representations |
| Speaker | 5 | George Jeffreys | Quantum Finite Automata and Quiver Algebras |
| SESSION 11 | Topic 5 | INFORMATION GEOMETRY AND PHYSICS | CHAIRS: ARIEL CATICHA & ALI DJAFARI |
| Invited speaker 09 | 88 | Pierre-Henri Wuillemin | Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks |
| Speaker | 13 | Jean-Claude Zambrini | Hamilton-Jacobi-Bellman equations in Stochastic Geometric Mechanics |
| Speaker | 40 | Noémie Combe | Poisson geometry of the statistical Frobenius manifold. |
| Speaker | 43 | Jean-Pierre Françoise, Daisuke Tarama | Dynamical systems over Lie groups associated to statistical transformation models |
| Speaker | 44 | Andrew Beckett | Homogeneous Symplectic Spaces and Central Extensions |
| Speaker | 57 | Frederic Barbaresco | Souriau Maximum Entropy Statistical Distribution for Homogeneous Bounded Domains: Poincaré and Siegel Disks |
| Speaker | 25 | Michel Nguiffo Boyom | Relevant foliations and topological persistence in statistical manifolds |
| Speaker | 29 | Valerie Girardin | On the Asymptotic Classification of Generalized Entropies |
| Speaker | 39 | Stefan Behringer | The Value of Information in Circular Settings |
| Speaker | 58 | Carlos Alcalde | Information Geometry In Phase Space |
| Friday July 22 | |||
| SESSION 12 | Topic 3 | INFERENCE AND ENTROPY | CHAIRS: OLIVIER RIOUL & ALI DJAFARI |
| Invited speaker 10 | 1 | Siddhartha Chib, Minchul Shin and Anna Simoni | Bayesian Exponentially Tilted Empirical Likelihood to Endogeneity Testing |
| 3 | Frank Nielsen | Information measures and information geometry of the Zeta and Lattice Gaussian MaxEnt Distributions | |
| Speaker | 41 | Fabio Di Nocera | Unfolding of relative entropies and monotone metrics |
| Speaker | 42 | Shlomo Dubnov and Gerard Assayag | Switching Machine Improvisation Models by Latent Transfer Entropy Criteria |
| SESSION 13 | Topic 3 | BAYESIAN METHODS FOR IMAGING | CHAIRS: YANNIS KALAIDZIDIS & MARIA TROCAN |
| Invited speaker 11 | 11 | Fabrizia Guglielmetti | Bayesian and Machine Learning Methods in the Big Data era for astronomical imaging. |
| Speaker | 24 | Phillip Frank | Geometric Variational Inference and its application to Bayesian imaging |
| Speaker | 62 | Harry Bevins | Marginal Bayesian Statistics Using Masked Autoregressive Flows and Kernel Density Estimators with Examples in Cosmology |
| SESSION 14 | Topic 2 | GRAPHICAL AND GEOMETRICAL LEARNING | CHAIRS: ENSSLIN TORSTEN & ALI DJAFARI |
| Invited speaker 12 | 73 | Piotr Graczyk, Hideyuki Ishi and Bartosz Kolodziejek | Graphical Gaussian models associated to a homogeneous graph with permutation symmetries |
| Speaker | 37 | Michel Broniatowski and Wolfgang Stummer | A precise bare simulation approach to generalized entropy maximization |
| Speaker | 15 | Sascha Ranftl | A connection between probability, physics and neural networks |
| SESSION 15 | Topic 2 | LEARNING, SURROGATE MODELS AND INFORMATION | CHAIRS: ROBERT NIVEN & ALI DJAFARI |
| Speaker | 7 | Filippo Masi and Ioannis Stefanou | Data- and thermodynamics-driven discovery of state variables and evolution equations |
| Speaker | 9 | Beatriz Moya, Quercus Hernandez, Alebrto Badias, Francisco Chinesta and Elias Cueto | Thermodynamics of learning physical phenomena |
| Speaker | 63 | Patricia Conde-Cespedes, Guillaume Lachaud and Maria Trocan | The Role of Entropy in Machine Learning and Applications |
| Speaker | 48 | Roland Preuss and Udo von Toussaint | SURROGATE MODELLING OF ION-SOLID INTERACTION SIMULATIONS |
| Speaker | 85 | Olivier Peltre | Local Max-Entropy and Free Energy Principles solved by Belief Propagation |
| Speaker | 68 | Adrian Josue Guel Cortez and Eun-jin Kim | Information geometry under the Laplace assumption |
| Speaker | 22 | Romke Bontekoe and Barrie J. Stokes | Kangaroos in Cambridge |
Poster session
| 12 | Screening of the synthesis route on the structural, magnetic and magnetocaloric properties of La0.6Ca0.2Ba0.2MnO3 manganite: A comparison between solid-solid state process and a combination polyol process and Spark Plasma Sintering |
| 18 | Modelling of aortic dissection with Beta random fields and uncertainty propagation with a Bayesian variational auto-encoder |
| 26 | Infrared Temperature reconstruction based on Bayesian Varational Approximation |
| 33 | A Computational Model to Determine Membrane Ionic Conductance Using Electroencephalography in Epilepsy |
| 45 | Maxwell's demon and information theory in market efficiency: A Brillouin's perspective |
| 47 | Digital computing through randomness and order in neural networks |
| 53 | Strategies of choosing the regularization parameter in Bayesian approach to image reconstruction in nuclear medicine |
| 54 | Attention guided multi-scale CNN Network for Cervical Vertebral Maturation Assessment from Lateral Cephalometric Radiography |
| 56 | Maximum Entropy Regularization and TLBO in the Medical Imaging Problems |
| 59 | Upscaling Reputation Communication Simulations |
| 61 | Variational Bayesian Approximation (VBA): A comparison between three optimization algorithms |
| 64 | SEIR modeling, simulation, parameter estimation, and its application for Covid-19 epidemic prediction |
| 66 | The efficient representation of spatially variant point spread functions in Bayesian imaging algorithms |
| 82 | Coherence-impurity complementarity for quantum systems using entropies and majorization |
| 77 | Bayesian fusion of infrared image and visible image with a hierarchical Gaussian mixture model |
| 78 | Curiosity driven exploration with perspective taking |
| 89 | Multiobjective Optimization Of The Nanocavities Diffusion In Irradiated Metals |
| 90 | Are Central Bankers Inflation Nutters? A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model |
[table “” not found /]