quantile regression

A unifying partially-interpretable framework for neural network-based extreme quantile regression

Raphaël Huser, Associate Professor, Statistics

Nov 29, 12:00 - 13:00

B9 L2 R2322

Artificial Neural Network quantile regression

In this paper, we propose a new methodological framework for performing extreme quantile regression using artificial neural networks, which are able to capture complex non-linear relationships and scale well to high-dimensional data.

Joydeep Chowdhury

Postdoctoral Research Fellow, Statistics

functional data analysis multivariate analysis spatial statistics quantile regression non-parametric methods

Joydeep Chowdhury is a postdoctoral fellow in the Spatio-Temporal Statistics & Data Science research group of Professor Marc G. Genton. His current research activities focus on problems in multivariate statistics, spatial statistics and functional data analysis.