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Nombre de programmes trouvés : 544

le (56m47s)


Combining the principles of general relativity and quantum theory still remains as elusive as ever. Recent work, that concentrated on the points of conflict and contact between quantum theory and general relativity, suggests a new perspective on gravity. It appears that the field equations of gravity in a wide class of theories - including, but not limited to, standard Einstein's theory - can be given a purely thermodynamic interpretation. In this approach gravity appears as an emergent phenomenon, like e.g., gas or fluid dynamics. I ...
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le (56m22s)

Inférence à la meilleure explication en mathématiques : Concilier apriorité et révisabilité / Mathematical inference to the best explanation : Reconciling a priority and revisability.

... explication en mathématiques. Peut-on, en mathématiques, avoir des formes à priori d’inférence à la meilleure explication ? Peuvent-elles être à la fois à priori et révisables ? Marina Imocrante discusses the nature of mathematical inferences to the...
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le (56m5s)

Eternal family trees and dynamics on unimodular random graphs (workshop ERC Nemo Processus ponctuels et graphes aléatoires unimodulaires)

This talk is centered on covariant dynamics on unimodular random graphs and random networks (marked graphs), namely maps from the set of vertices to itself which are preserved by graph or network isomorphisms. Such dynamics are referred to as vertex-shifts here. These dynamics have point-shifts on point processes as a subclass. First we give a classification of vertex-shifts on unimodular random networks. Each such vertex-shift partitions the vertices into a collection of connected components and foils. The latter are discrete analogues the stable manifold ...
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le (55m56s)

A notion of entropy for limits of sparse marked graphs (workshop ERC Nemo Processus ponctuels et graphes aléatoires unimodulaires)

Bordenave and Caputo (2014) defined a notion of entropy for probability distributions on rooted graphs with finite expected degree at the root. When such a probability distribution \rho has finite BC entropy \Sigma(\rho), the growth in the number of vertices n of the number of graphs on n vertices whose associated rooted graph distribution is close to \rho is as d/2 n \log n + \Sigma(\rho) n + o(n), where d is expected degree of the root under \rho. We develop the parallel result for probability distributions on marked rooted graphs. Our graphs have vertex marks drawn from a finite ...
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