Multivariate Uncertainty Quantification with Tomographic Quantile Forests
Quantifying predictive uncertainty is essential for safe and trustworthy real-world AI deployment. However, the fully nonparametric estimation of conditional distributions remains challenging for multivariate targets. We propose Tomographic Quantile Forests (TQF), a nonparametric, uncertainty-aware,...
Na minha lista:
| Autor principal: | |
|---|---|
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2026-04-01
|
| coleção: | Mathematical and Computational Applications |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2297-8747/31/2/53 |
| Tags: |
Sem tags, seja o primeiro a adicionar uma tag!
|