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Autoregressive Quantile Flows for Predictive Uncertainty ...
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由 P Si 著作被引用 17 次 — We propose autoregressive quantile flows, a flexible class of normalizing flow models trained using a novel objective based on proper scoring rules.
Autoregressive Quantile Flows for Predictive Uncertainty ...
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由 P Si 著作2021被引用 17 次 — We propose autoregressive quantile flows, a flexible class of normalizing flow models trained using a novel objective based on proper scoring rules.
AUTOREGRESSIVE QUANTILE FLOWS FOR ...
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由 P Si 著作2021被引用 17 次 — We use AQFs as the basis for quantile flow regression (QFR), an approach to predictive uncertainty estimation in which a probabilistic model directly outputs a ...
Autoregressive Quantile Flows for Predictive Uncertainty ...
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This work proposes autoregressive quantile flows, a flexible class of normalizing flow models trained using a novel objective based on proper scoring rules ...
Calibration Metrics and Accuracy
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We propose Autoregressive Quantile Flows, a flexible class of probabilistic models over high-dimensional variables that can be used to accurately capture ...
hanlaoshi/Deep-Generative-Modeling
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These authors propose autoregressive quantile flows, a flexible class of normalizing flow models trained using a novel objective based on proper scoring rules.
Results on the object detection task
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We propose Autoregressive Quantile Flows, a flexible class of probabilistic models over high-dimensional variables that can be used to accurately capture ...
arXiv:2112.07184v2 [cs.LG] 19 Sep 2022
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由 V Kuleshov 著作2021被引用 30 次 — Autoregressive quantile flows for predictive uncertainty estimation, 2021. Song, H., Diethe, T., Kull, M., and Flach, P. Distribution.
Phillip Si
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Autoregressive Quantile Flows for Predictive Uncertainty Estimation ... Numerous applications of machine learning involve representing probability distributions ...
Phillip Si - Google 学术搜索
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Autoregressive quantile flows for predictive uncertainty estimation. P Si, A Bishop, V Kuleshov. International Conference on Learning Representations, 2022. 17 ...