Search Results for author: Olivier Peltre

Found 5 papers, 4 papers with code

Local Max-Entropy and Free Energy Principles, Belief Diffusions and their Singularities

1 code implementation4 Oct 2023 Olivier Peltre

A comprehensive picture of three Bethe-Kikuchi variational principles including their relationship to belief propagation (BP) algorithms on hypergraphs is given.

Local Max-Entropy and Free Energy Principles Solved by Belief Propagation

no code implementations2 Jul 2022 Olivier Peltre

A statistical system is classically defined on a set of microstates $E$ by a global energy function $H : E \to \mathbb{R}$, yielding Gibbs probability measures (softmins) $\rho^\beta(H)$ for every inverse temperature $\beta = T^{-1}$.

Belief Propagation as Diffusion

1 code implementation26 Jul 2021 Olivier Peltre

We introduce novel belief propagation algorithms to estimate the marginals of a high dimensional probability distribution.

Geomstats: A Python Package for Riemannian Geometry in Machine Learning

1 code implementation ICLR 2019 Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec

We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matrices, Lie groups of transformations, and many more.

BIG-bench Machine Learning Clustering +2

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