CredibleDFGO extends DFGO by training a weighting network with NLL and energy score supervision so that the Hessian-derived covariances better match actual positioning errors on UrbanNav scenes.
Victor Dheur and Souhaib Ben Taieb
2 Pith papers cite this work, alongside 153 external citations. Polarity classification is still indexing.
2
Pith papers citing it
153
external citations · OpenAlex
representative citing papers
Systematic benchmarking reveals that regression calibration metrics frequently disagree on recalibration quality, with ENCE and CWC identified as more consistent performers.
citing papers explorer
-
CredibleDFGO: Differentiable Factor Graph Optimization with Credibility Supervision
CredibleDFGO extends DFGO by training a weighting network with NLL and energy score supervision so that the Hessian-derived covariances better match actual positioning errors on UrbanNav scenes.
-
Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models
Systematic benchmarking reveals that regression calibration metrics frequently disagree on recalibration quality, with ENCE and CWC identified as more consistent performers.