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 ...

📢 Big News: We are going LIVE with code! Diffusion models aren't just for generating images -- they are a powerful tool for scientific inference. On Feb 9, I’m hosting Jonas Arruda on the Learning Ba...

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...

Contains the code accompanying the paper "Sensitivity-Aware Amortized Bayesian Inference". - bayesflow-org/SA-ABI

Bayesian inference usually requires running potentially costly inference procedures separately for every new observation. In contrast, the idea of amortized Bayesian inference is to initially invest c...