8 citations · 26 across the 11 of their papers we have counts for
12 papers
Characteristic Neural Ordinary Differential Equations
Xingzi Xu, Ali Hasan, Khalil Elkhalil +2
We propose Characteristic-Neural Ordinary Differential Equations (C-NODEs), a framework for extending Neural Ordinary Differential Equations (NODEs) beyond ODEs. While NODEs model…
Generative Archimedean Copulas
Yuting Ng, Ali Hasan, Khalil Elkhalil +1
We propose a new generative modeling technique for learning multidimensional cumulative distribution functions (CDFs) in the form of copulas. Specifically, we consider certain clas…
Modeling Extremes with d-max-decreasing Neural Networks
Ali Hasan, Khalil Elkhalil, Yuting Ng +4
We propose a novel neural network architecture that enables non-parametric calibration and generation of multivariate extreme value distributions (MEVs). MEVs arise from Extreme Va…
Fisher Auto-Encoders
Khalil Elkhalil, Ali Hasan, Jie Ding +2
It has been conjectured that the Fisher divergence is more robust to model uncertainty than the conventional Kullback-Leibler (KL) divergence. This motivates the design of a new cl…
Improved Design of Quadratic Discriminant Analysis Classifier in Unbalanced Settings
Amine Bejaoui, Khalil Elkhalil, Abla Kammoun +2
The use of quadratic discriminant analysis (QDA) or its regularized version (R-QDA) for classification is often not recommended, due to its well-acknowledged high sensitivity to th…
Risk Convergence of Centered Kernel Ridge Regression with Large Dimensional Data
Khalil Elkhalil, Abla Kammoun, Xiangliang Zhang +2
This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call \emph{centered kernel ridge regression} (CKRR), also known in the literat…