Zobrazeno 1 - 10
of 49
pro vyhledávání: '"de Panafieu, Élie"'
Autor:
de Panafieu, Élie
We derive the asymptotic expansion (asymptotics with an arbitrary number of error terms) of k-regular graphs by applying the Laplace method on a recent exact formula from Caizergues and de Panafieu (2023). We also deduce the asymptotic expansion of c
Externí odkaz:
http://arxiv.org/abs/2408.12459
We consider an Erd\H{o}s-R\'enyi random graph, conditioned on the rare event that all connected components are fully connected. Such graphs can be considered as partitions of vertices into cliques. Hence, this conditional distribution defines a distr
Externí odkaz:
http://arxiv.org/abs/2405.13454
Autor:
Hainzl, Eva-Maria, de Panafieu, Élie
It is a classic result in spectral theory that the limit distribution of the spectral measure of random graphs G(n, p) converges to the semicircle law in case np tends to infinity with n. The spectral measure for random graphs G(n, c/n) however is le
Externí odkaz:
http://arxiv.org/abs/2405.08347
We consider the design of a positioning system where a robot determines its position from local observations. This is a well-studied problem of considerable practical importance and mathematical interest. The dominant paradigm derives from the classi
Externí odkaz:
http://arxiv.org/abs/2404.09981
Autor:
de Panafieu, Élie, Wallner, Michael
This paper introduces nondeterministic walks, a new variant of one-dimensional discrete walks. The main difference to classical walks is that its nondeterministic steps consist of sets of steps from a predefined set such that all possible extensions
Externí odkaz:
http://arxiv.org/abs/2311.03234
Publikováno v:
NeurIPS 2021
Gathering training data is a key step of any supervised learning task, and it is both critical and expensive. Critical, because the quantity and quality of the training data has a high impact on the performance of the learned function. Expensive, bec
Externí odkaz:
http://arxiv.org/abs/2110.14521
We obtain exact expressions counting the satisfiable 2-SAT formulae and describe the structure of associated implication digraphs. Our approach is based on generating function manipulations. To reflect the combinatorial specificities of the implicati
Externí odkaz:
http://arxiv.org/abs/2108.08067
Autor:
Durand, François, de Panafieu, Élie
Consider two random variables following Skellam distributions of parameters going to infinity linearly. We prove that the limit distribution of the first variable, conditionally on being equal to the second, is Gaussian.
Comment: 7 pages
Comment: 7 pages
Externí odkaz:
http://arxiv.org/abs/2102.10835
Autor:
Dovgal, Sergey, de Panafieu, Élie, Ralaivaosaona, Dimbinaina, Rasendrahasina, Vonjy, Wagner, Stephan
Random directed graphs $D(n,p)$ undergo a phase transition around the point $p = 1/n$, and the width of the transition window has been known since the works of Luczak and Seierstad. They have established that as $n \to \infty$ when $p = (1 + \mu n^{-
Externí odkaz:
http://arxiv.org/abs/2009.12127
Autor:
de Panafieu, Élie, Dovgal, Sergey
Directed acyclic graphs (DAGs) can be characterised as directed graphs whose strongly connected components are isolated vertices. Using this restriction on the strong components, we discover that when $m = cn$, where $m$ is the number of directed edg
Externí odkaz:
http://arxiv.org/abs/2001.08659