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,...
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| Hlavní autor: | |
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| Médium: | Artigo |
| Jazyk: | Inglês |
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MDPI AG
2026-04-01
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| Edice: | Mathematical and Computational Applications |
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| On-line přístup: | https://www.mdpi.com/2297-8747/31/2/53 |
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