70%Highly rated
?Highly ratedVote to see the score
Partition Tree: Conditional Density Estimation over General Outcome Spaces
Partition Tree is a tree-based framework for conditional density estimation over general outcome spaces that learns by minimizing negative log-likelihood. It yields a scalable nonparametric alternative to probabilistic trees with improved predictive performance.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
– ReadersNo votes yet
4/20 AI panelreviewers recommend it
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.
AI panel: 4 of 20 reviewers recommend it
lenient 3/5
medium 1/10
strict 0/5