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Trust your neighbours: Penalty-based constraints for model calibration

Trust your neighbours: Penalty-based constraints for model calibration

11 March 2023
Balamurali Murugesan
V. SukeshAdiga
Bingyuan Liu
H. Lombaert
Ismail Ben Ayed
Jose Dolz
    UQCV
ArXivPDFHTML

Papers citing "Trust your neighbours: Penalty-based constraints for model calibration"

3 / 3 papers shown
Title
Class and Region-Adaptive Constraints for Network Calibration
Class and Region-Adaptive Constraints for Network Calibration
Balamurali Murugesan
Julio Silva-Rodríguez
Ismail Ben Ayed
Jose Dolz
27
1
0
19 Mar 2024
Boundary-weighted logit consistency improves calibration of segmentation
  networks
Boundary-weighted logit consistency improves calibration of segmentation networks
Neerav Karani
Neel Dey
Polina Golland
17
3
0
16 Jul 2023
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
252
9,134
0
06 Jun 2015
1