66 citations · 258 across the 53 of their papers we have counts for
5 papers · 1 filter
Deep Learning applied to Road Traffic Speed forecasting
Thomas Epelbaum, Fabrice Gamboa, Jean-Michel Loubes +1
In this paper, we propose deep learning architectures (FNN, CNN and LSTM) to forecast a regression model for time dependent data. These algorithm's are designed to handle Floating…
Connecting pairwise spheres by depth: DCOPS
Ricardo Fraiman, Fabrice Gamboa, Leonardo Moreno
We extend the classical notion of the spherical depth in \mathbb{R}^k, to the important setup of data on a Riemannian manifold. We show that this notion of depth satisfies a set of…
Approximate Optimal Designs for Multivariate Polynomial Regression
Yohann De Castro, Fabrice Gamboa, Didier Henrion +2
We introduce a new approach aiming at computing approximate optimal designs for multivariate polynomial regressions on compact (semi-algebraic) design spaces. We use the moment-sum…
D-optimal design for multivariate polynomial regression via the Christoffel function and semidefinite relaxations
Yohann De Castro, F Gamboa, D Henrion +2
We present a new approach to the design of D-optimal experiments with multivariate polynomial regressions on compact semi-algebraic design spaces. We apply the moment-sum-of-square…
A Gaussian Process Regression Model for Distribution Inputs
François Bachoc, Fabrice Gamboa, Jean-Michel Loubes +1
Monge-Kantorovich distances, otherwise known as Wasserstein distances, have received a growing attention in statistics and machine learning as a powerful discrepancy measure for pr…