MCMC re-runs from scratch on every new dataset. Amortized Bayesian inference pays the cost once -- then gives you a posterior in milliseconds, forever. Stefan Radev (BayesFlow creator) and I built an ...

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

Coding agents confidently say "X causes Y" without drawing a DAG, checking assumptions, or running refutation tests. I built an Agent Skill that won't let them. 100% eval pass rate vs 68% without -- t...

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

A researcher stress-tested my Bayesian Agent Skill on a real hierarchical model. It caught the workflow violations but missed a subtle prediction bug, had no sparsity priors, and lacked classification...

Teach your AI coding agent to think like a Bayesian. Discover the bayesian-workflow Agent Skill that prevents subtle statistical errors in PyMC models.

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

Diffusion models have recently emerged as powerful learners for simulation-based inference (SBI), enabling fast and accurate estimation of latent parameters from simulated and real data. Their score-b...

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written by Eric J. Ma on 2025-12-28 | tags: ai opencode claude automation workflow llm reasoning development review tools

**State Space Models** (SSMs) are powerful tools for time series analysis, widely used in finance, economics, ecology, and engineering. They allow researchers t... By Alexandre Andorra, Jesse Grabowsk...

Statistical machine learning is powering groundbreaking advances, yet uncertainty quantification remains one of its biggest challenges.

Statistical machine learning is powering groundbreaking advances, yet uncertainty quantification remains one of its biggest challenges.