UncertaintyBayes

Uncertainty estimation and distributed prediction kit

Product category: Probabilistic prediction

Applicable platforms: PyTorch, NumPyro

Technical affiliation: Bayesian, Ensemble, Quantile Loss

Programming language affiliation: Python

Tags: #Uncertainty #BayesianML Product

Type: Probabilistic prediction

UncertaintyBayes provides confidence intervals and risk characterization for predictions, supporting quantile regression, Monte Carlo Dropout, deep ensembles, and Bayesian regression, and provides temperature scaling and calibration evaluation. For time series projects, it can quantify future uncertainty; for multimodal projects, it gives cross-modality confidence fusion; for policy/decision, it provides risk penalties and conservative strategy switching thresholds. It engineering passes "credibility" to the decision chain, avoiding systemic risks from model overconfidence.

Delivery method: Instant digital download after purchase
License: Single-user commercial license
Usage limit: One-time use
Support: Technical documentation provided in the delivery file; no human technical support included