Évènement

Sixin Zhang
IRIT, Toulouse
https://www.di.ens.fr/~zhang/

Date(s) : 06/03/2020   iCal
14h00 - 15h00

We define maximum-entropy models of stationary processes from non-linear representations. To capture coherent structures in a random process such as Turbulent flows, we focus on the problemof choosing sufficient statistical moments. It amounts to find features corresponding to the statistical patterns of coherent structures. A new set of covariance moments are learnt-by-hand over the last few years. It brings about a conceptual connection betweenthe rectifier non-linearity in convolutional neural networks and the phase in Fourier and wavelet representations. We conjecture that structures in the phase play a key role for pattern recognition and high-dimensional data modeling.

Emplacement
I2M Chateau-Gombert - CMI, Salle de Séminaire R164 (1er étage)

Catégories

• Séminaire