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Introducing an Improved Information-Theoretic Measure of Predictive
  Uncertainty

Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty

14 November 2023
Kajetan Schweighofer
L. Aichberger
Mykyta Ielanskyi
Sepp Hochreiter
ArXivPDFHTML

Papers citing "Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty"

11 / 11 papers shown
Title
Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition
Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition
Arthur Hoarau
Benjamin Quost
Sébastien Destercke
Willem Waegeman
UQCV
UD
PER
61
0
0
30 Jan 2025
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Johan Hatleskog
Kostas Alexis
3DPC
32
2
0
14 Oct 2024
Semantically Diverse Language Generation for Uncertainty Estimation in
  Language Models
Semantically Diverse Language Generation for Uncertainty Estimation in Language Models
L. Aichberger
Kajetan Schweighofer
Mykyta Ielanskyi
Sepp Hochreiter
HILM
28
10
0
06 Jun 2024
Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring
  Rules
Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring Rules
Paul Hofman
Yusuf Sale
Eyke Hüllermeier
UQCV
UD
PER
38
5
0
18 Apr 2024
Predictive Uncertainty Quantification via Risk Decompositions for
  Strictly Proper Scoring Rules
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules
Nikita Kotelevskii
Maxim Panov
PER
UQCV
UD
22
3
0
16 Feb 2024
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep
  Learning Methods?
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
Mira Jürgens
Nis Meinert
Viktor Bengs
Eyke Hüllermeier
Willem Waegeman
UQCV
UD
PER
EDL
BDL
27
11
0
14 Feb 2024
Second-Order Uncertainty Quantification: A Distance-Based Approach
Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale
Viktor Bengs
Michele Caprio
Eyke Hüllermeier
PER
UQCV
UD
22
18
0
02 Dec 2023
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from
  Spatial Aleatoric Uncertainty
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty
Kilian Zepf
Selma Wanna
M. Miani
Juston Moore
J. Frellsen
Søren Hauberg
Aasa Feragen
Frederik Warburg
UQCV
27
4
0
23 Mar 2023
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in
  Gaussian Process Hybrid Deep Networks
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
John Bradshaw
A. G. Matthews
Zoubin Ghahramani
BDL
AAML
60
171
0
08 Jul 2017
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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