SA-BCP achieves optimal spatio-temporal decoupling in Bayesian conformal prediction by gating temporal inertia with spatial kernel-density evidence, governed by a minimax bias-variance threshold K, and outperforms ACI and Bayesian CP baselines on financial datasets.
Advances in Neural Information Processing Systems: Workshop on Bayesian Decision-making and Uncertainty , year=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Optimal Spatio-Temporal Decoupling for Bayesian Conformal Prediction
SA-BCP achieves optimal spatio-temporal decoupling in Bayesian conformal prediction by gating temporal inertia with spatial kernel-density evidence, governed by a minimax bias-variance threshold K, and outperforms ACI and Bayesian CP baselines on financial datasets.