Conditional Density Estimation with Deep Neural Networks

Estimating conditional density functions is a fundamental problem in statistics.This task is crucial for understanding the underlying relationships between variables and for making informed predictions in various applications.In this paper, we introduce a novel deep nonparametric approach for estimating conditional density functions from data.Our method leverages the flexibility and expressiveness of deep neural networks to model the conditional density without imposing restrictive parametric as