An uncertainty-aware Bayesian framework for machine learning classification models: A case study in land cover classification 事件

An uncertainty-aware Bayesian framework for machine learning classification models: A case study in land cover classification arXiv:2503.21510v3 Announce Type: replace-cross Abstract: Ensuring that predictions of machine learning (ML) classification models are accompanied by uncertainty estimates is one of the main pillars of trustworthy AI. Current research in uncertainty quantification focuses mainly on epistemic uncertainty of the ML model, but rarely takes account of input measurement uncer