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ORCIDSPIGL 2020: Les Houches, France
- Frédéric Barbaresco, Frank Nielsen:
Geometric Structures of Statistical Physics, Information Geometry, and Learning - SPIGL'20, Les Houches, France, July 27-31. Springer 2021, ISBN 978-3-030-77956-6
Part I: Tribute to Jean-Marie Souriau Seminal Works
- Géry de Saxcé, Charles-Michel Marle:
Structure des Systèmes Dynamiques Jean-Marie Souriau's Book 50th Birthday. 3-11 - Frédéric Barbaresco:
Jean-Marie Souriau's Symplectic Model of Statistical Physics: Seminal Papers on Lie Groups Thermodynamics - Quod Erat Demonstrandum. 12-50
Part II: Lie Group Geometry and Diffeological Model of Statistical Physics and Information Geometry
- Frédéric Barbaresco:
Souriau-Casimir Lie Groups Thermodynamics and Machine Learning. 53-83 - Koichi Tojo, Taro Yoshino:
An Exponential Family on the Upper Half Plane and Its Conjugate Prior. 84-95 - Emmanuel Chevallier, Nicolas Guigui:
Wrapped Statistical Models on Manifolds: Motivations, The Case SE(n), and Generalization to Symmetric Spaces. 96-106 - Géry de Saxcé:
Galilean Thermodynamics of Continua. 107-119 - Hông Vân Lê, Alexey A. Tuzhilin:
Nonparametric Estimations and the Diffeological Fisher Metric. 120-138
Part III: Advanced Geometrical Models of Statistical Manifolds in Information Geometry
- Jean-Pierre Françoise:
Information Geometry and Integrable Hamiltonian Systems. 141-153 - Michel Nguiffo Boyom:
Relevant Differential Topology in Statistical Manifolds. 154-178 - Giovanni Pistone:
A Lecture About the Use of Orlicz Spaces in Information Geometry. 179-195 - Frank Nielsen
, Gaëtan Hadjeres:
Quasiconvex Jensen Divergences and Quasiconvex Bregman Divergences. 196-218
Part IV: Geometric Structures of Mechanics, Thermodynamics and Inference for Learning
- Hiroaki Yoshimura, François Gay-Balmaz:
Dirac Structures and Variational Formulation of Thermodynamics for Open Systems. 221-246 - Alexandre Anahory Simoes, David Martín de Diego, Manuel Lainz Valcázar, Manuel de León:
The Geometry of Some Thermodynamic Systems. 247-275 - Francisco Chinesta, Elías Cueto, Miroslav Grmela, Beatriz Moya, Michal Pavelka, Martin Sípka:
Learning Physics from Data: A Thermodynamic Interpretation. 276-297 - Zdravko Terze, Viktor Pandza, Marijan Andric, Dario Zlatar:
Computational Dynamics of Reduced Coupled Multibody-Fluid System in Lie Group Setting. 298-307 - Filippo Masi, Ioannis Stefanou, Paolo Vannucci, Victor Maffi-Berthier:
Material Modeling via Thermodynamics-Based Artificial Neural Networks. 308-329 - Kevin T. Grosvenor:
Information Geometry and Quantum Fields. 330-341
Part V: Hamiltonian Monte Carlo, HMC Sampling and Learning on Manifolds
- Alessandro Barp:
Geometric Integration of Measure-Preserving Flows for Sampling. 345-355 - Anis Fradi, Ines Adouani, Chafik Samir:
Bayesian Inference on Local Distributions of Functions and Multidimensional Curves with Spherical HMC Sampling. 356-373 - Steve Huntsman:
Sampling and Statistical Physics via Symmetry. 374-427 - Thomas Gerald, Hadi Zaatiti, Hatem Hajri:
A Practical Hands-on for Learning Graph Data Communities on Manifolds. 428-459
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