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Marginally-calibrated deep distributional regression

Marginally-calibrated deep distributional regression

26 August 2019
Nadja Klein
David J. Nott
M. Smith
    UQCV
ArXivPDFHTML

Papers citing "Marginally-calibrated deep distributional regression"

6 / 6 papers shown
Title
A review of predictive uncertainty estimation with machine learning
A review of predictive uncertainty estimation with machine learning
Hristos Tyralis
Georgia Papacharalampous
UD
UQCV
51
42
0
17 Sep 2022
A review of machine learning concepts and methods for addressing
  challenges in probabilistic hydrological post-processing and forecasting
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting
Georgia Papacharalampous
Hristos Tyralis
AI4CE
27
28
0
17 Jun 2022
Deep Distributional Time Series Models and the Probabilistic Forecasting
  of Intraday Electricity Prices
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices
Nadja Klein
M. Smith
David J. Nott
BDL
AI4TS
14
24
0
05 Oct 2020
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
74
266
0
13 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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