Fast Bayesian Inference in Python. 50+ conjugate models with vectorized updates, sufficient statistic helpers, built-in plotting, and SciPy integration.
Conjugate Bayesian linear regression and distribution models in Python.
Exact Bayesian trust and reputation scoring for tools, MCP servers, skills, and agents. Zero-dependency, TypeScript-first: closed-form Beta-Bernoulli posteriors, calibrated credible intervals, Thompson-sampling routing, time-decay, and a tamper-evident audit trail.
Thompson-sampling Bayesian router that picks the right LLM per query across quality, cost, and latency. Zero-dependency, TypeScript-first, with exact conjugate posteriors, safe exploration, and bounded regret.
Homework for the course Statistical Methods for Data Science @ La Sapienza University of Rome a.y. 2022/23
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