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pro vyhledávání: '"Mordant P"'
The quadratically regularized optimal transport problem has recently been considered in various applications where the coupling needs to be \emph{sparse}, i.e., the density of the coupling needs to be zero for a large subset of the product of the sup
Externí odkaz:
http://arxiv.org/abs/2407.21528
We describe laboratory experiments in a 2D wave tank that aim at building up and monitor 2D shallow water soliton gas. The water surface elevation is obtained over a large ($\sim 100\,\text{m}^2$) domain, with centimetre-resolution, by stereoscopic v
Externí odkaz:
http://arxiv.org/abs/2405.14733
We propose a new metric between probability measures on a compact metric space that mirrors the Riemannian manifold-like structure of quadratic optimal transport but includes entropic regularization. Its metric tensor is given by the Hessian of the S
Externí odkaz:
http://arxiv.org/abs/2405.04987
Autor:
Mordant, Thomas
Publikováno v:
Math. Z. (2024), 306(4): Paper No. 67, 19 pp
In this note, we give sufficient conditions for the (semi)stability of a hypersurface $H$ of $\mathbb{P}^N_k$ in terms of its degree $d$, the maximal multiplicity $\delta$ of its singularities, and the dimension $s$ of its singular locus. For instanc
Externí odkaz:
http://arxiv.org/abs/2312.09774
Autor:
Rodda, Costanza, Savaro, Clément, Bouillaut, Vincent, Augier, Pierre, Sommeria, Joël, Valran, Thomas, Viboud, Samuel, Mordant, Nicolas
We report on the statistical analysis of stratified turbulence forced by large-scale waves. The setup mimics some features of the tidal forcing of turbulence in the ocean interior at submesoscales. Our experiments are performed in the large-scale Cor
Externí odkaz:
http://arxiv.org/abs/2311.13476
Autor:
Mordant, Gilles
We investigate the link between regularised self-transport problems and maximum likelihood estimation in Gaussian mixture models (GMM). This link suggests that self-transport followed by a clustering technique leads to principled estimators at a reas
Externí odkaz:
http://arxiv.org/abs/2310.14851
Autor:
Dosenovic, D., Sharma, K., Dechamps, S., Rouviere, J. -L., Lu, Y., Mordant, A., Hertog, M. den, Genovese, L., Dubois, S. M. -M., Charlier, J. -C., Jamet, M., Marty, A., Okuno, H.
There has been extensive activity exploring the doping of semiconducting two-dimensional (2D) transition metal dichalcogenides in order to tune their electronic and magnetic properties. The outcome of doping depends on various factors, including the
Externí odkaz:
http://arxiv.org/abs/2310.09246
Autor:
Jian Zou, Elizabeth McNair, Sagan DeCastro, Scott P. Lyons, Angie Mordant, Laura E. Herring, Ryan P. Vetreno, Leon G. Coleman Jr
Publikováno v:
Journal of Neuroinflammation, Vol 21, Iss 1, Pp 1-19 (2024)
Abstract Background Alzheimer’s disease (AD) features progressive neurodegeneration and microglial activation that results in dementia and cognitive decline. The release of soluble amyloid (Aβ) oligomers into the extracellular space is an early fe
Externí odkaz:
https://doaj.org/article/b6ac96edff3a4a2cb1ff1b8d4cb09b75
Manifold learning is a central task in modern statistics and data science. Many datasets (cells, documents, images, molecules) can be represented as point clouds embedded in a high dimensional ambient space, however the degrees of freedom intrinsic t
Externí odkaz:
http://arxiv.org/abs/2307.09816
Optimal transport (OT) based data analysis is often faced with the issue that the underlying cost function is (partially) unknown. This paper is concerned with the derivation of distributional limits for the empirical OT value when the cost function
Externí odkaz:
http://arxiv.org/abs/2301.01287