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Quantifying Point-Prediction Uncertainty in Neural Networks via Residual
  Estimation with an I/O Kernel

Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel

3 June 2019
Xin Qiu
Elliot Meyerson
Risto Miikkulainen
    UQCV
ArXivPDFHTML

Papers citing "Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel"

9 / 9 papers shown
Title
Uncertainty Quantification Metrics for Deep Regression
Uncertainty Quantification Metrics for Deep Regression
Simon Kristoffersson Lind
Ziliang Xiong
Per-Erik Forssén
Volker Kruger
UQCV
34
3
0
07 May 2024
Scheduling Planting Time Through Developing an Optimization Model and
  Analysis of Time Series Growing Degree Units
Scheduling Planting Time Through Developing an Optimization Model and Analysis of Time Series Growing Degree Units
Javad Ansarifar
Faezeh Akhavizadegan
Lizhi Wang
14
1
0
02 Jul 2022
Image-to-Image Regression with Distribution-Free Uncertainty
  Quantification and Applications in Imaging
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging
Anastasios Nikolas Angelopoulos
Amit Kohli
Stephen Bates
Michael I. Jordan
Jitendra Malik
T. Alshaabi
S. Upadhyayula
Yaniv Romano
UQCV
OOD
14
94
0
10 Feb 2022
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Dongxian Wu
Liyao (Mars) Gao
X. Xiong
Matteo Chinazzi
Alessandro Vespignani
Yi Ma
Rose Yu
AI4TS
13
68
0
25 May 2021
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19
  forecasting
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting
Dongxian Wu
Liyao (Mars) Gao
X. Xiong
Matteo Chinazzi
Alessandro Vespignani
Yi Ma
Rose Yu
FedML
30
27
0
12 Feb 2021
Why have a Unified Predictive Uncertainty? Disentangling it using Deep
  Split Ensembles
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles
U. Sarawgi
W. Zulfikar
Rishab Khincha
Pattie Maes
PER
UQCV
BDL
UD
21
7
0
25 Sep 2020
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted
  Prescription
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription
Olivier Francon
Santiago Gonzalez
B. Hodjat
Elliot Meyerson
Risto Miikkulainen
Xin Qiu
H. Shahrzad
26
16
0
13 Feb 2020
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
276
5,683
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
287
9,156
0
06 Jun 2015
1