42 citations · 68 across the 8 of their papers we have counts for
10 papers
Joint parametric specification checking of conditional mean and volatility in time series models with martingale difference innovations
Kilani Ghoudi, Naâmane Laïb, Mohamed Chaouch
Using cumulative residual processes, we propose joint goodness-of-fit tests for conditional means and variances functions in the context of nonlinear time series with martingale di…
Generalized regression operator estimation for continuous time functional data processes with missing at random response
Mohamed Chaouch, Naâmane Laïb
In this paper, we are interested in nonparametric kernel estimation of a generalized regression function, including conditional cumulative distribution and conditional quantile fun…
LapNet : Automatic Balanced Loss and Optimal Assignment for Real-Time Dense Object Detection
Florian Chabot, Quoc-Cuong Pham, Mohamed Chaouch
Real-time single-stage object detectors based on deep learning still remain less accurate than more complex ones. The trade-off between model performance and computational speed is…
Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image
Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa +2
In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for many-task vehicle analysis from a given image. A robust convolutional network is introduced for…
Nonparametric M-estimation for right censored regression model with stationary ergodic data
Mohamed Chaouch, Naamane Laib, Elias Ould-Said
The present paper deals with a nonparametric M-estimation for right censored regression model with stationary ergodic data. Defined as an implicit function, a kernel type estimator…
Rate of uniform consistency for a class of mode regression on functional stationary ergodic data. Application to electricity consumption
Mohamed Chaouch, Naamane Laib, Djamal Louani
The aim of this paper is to study the asymptotic properties of a class of kernel conditional mode estimates whenever functional stationary ergodic data are considered. To be more p…