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.
After convergence, the solver returns the state estimate ˆX and the posterior covariance (Dellaert & Kaess, 2017), as indicated in Fig
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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.