Quantile regression has emerged as a significant extension of traditional linear models and its potential in survival applications has recently been recognized. In this paper we study quantile ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 46, No. 4 (1997), pp. 463-476 (14 pages) Patients infected with the human immunodeficiency virus (HIV) generally ...

Abstract: Quantile Regression (QR) can be used to estimate aleatoric uncertainty in deep neural networks and can generate prediction intervals. Quantifying uncertainty is particularly important in ...

This project aims to improve the accuracy and robustness of market risk measures using deep learning techniques. It targets two key metrics: Value at Risk (VaR): Probability-based downside risk ...

The kernel_quantile_regression package is an open source implementation of the quantile regressor technique introduced in [1]. This repo contains the code for reproducing the research paper ...