arXiv stat.ML
· Papers
Conditioning Tree-Based Diffusions and Flows for Probabilistic Tabular Regression
arXiv:2607.28864v1 Announce Type: new Abstract: Tree-based diffusion models fit flexible conditional predictive distributions for tabular regression without a neural density estimator, but they inherit their design defaults---noising path, parameterization, training distribution, features, sampler---from the neural set