CredibleDFGO adds explicit supervision of covariance credibility to differentiable factor graph optimization for GNSS by using proper scoring rules on the predictive distribution, yielding more trustworthy uncertainties on urban test scenes.
Proceedings of the 33rd International Conference on Machine Learning (ICML) , series =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
CredibleDFGO: Differentiable Factor Graph Optimization with Credibility Supervision
CredibleDFGO adds explicit supervision of covariance credibility to differentiable factor graph optimization for GNSS by using proper scoring rules on the predictive distribution, yielding more trustworthy uncertainties on urban test scenes.