Search Results for author:
Found 2 papers, 2 papers with code
Noise Regularization for Conditional Density Estimation
To address this issue, we develop a model-agnostic noise regularization method for CDE that adds random perturbations to the data during training.
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks
Given a set of empirical observations, conditional density estimation aims to capture the statistical relationship between a conditional variable $\mathbf{x}$ and a dependent variable $\mathbf{y}$ by modeling their conditional probability $p(\mathbf{y}|\mathbf{x})$.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
