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Post-hoc Models for Performance Estimation of Machine Learning Inference

Post-hoc Models for Performance Estimation of Machine Learning Inference

6 October 2021
Xuechen Zhang
Samet Oymak
Jiasi Chen
    UQCV
ArXivPDFHTML

Papers citing "Post-hoc Models for Performance Estimation of Machine Learning Inference"

4 / 4 papers shown
Title
Run-time Monitoring of 3D Object Detection in Automated Driving Systems
  Using Early Layer Neural Activation Patterns
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Hakan Yekta Yatbaz
M. Dianati
K. Koufos
Roger Woodman
3DPC
21
2
0
11 Apr 2024
Run-time Introspection of 2D Object Detection in Automated Driving
  Systems Using Learning Representations
Run-time Introspection of 2D Object Detection in Automated Driving Systems Using Learning Representations
Hakan Yekta Yatbaz
M. Dianati
K. Koufos
Roger Woodman
40
3
0
02 Mar 2024
From Black-box to White-box: Examining Confidence Calibration under
  different Conditions
From Black-box to White-box: Examining Confidence Calibration under different Conditions
Franziska Schwaiger
Maximilian Henne
Fabian Küppers
Felippe Schmoeller da Roza
Karsten Roscher
Anselm Haselhoff
34
10
0
08 Jan 2021
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
5,675
0
05 Dec 2016
1