Flow-ABI trains flow-matching models on historical data to produce a set-conditioned functional posterior sampler that delivers near-real-time Bayesian inference for regression and inverse PDE tasks without per-observation optimization.
Bayesflow: A probability inference framework for meta-agent assisted workflow generation.arXiv preprint arXiv:2601.22305, 2026
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Flow-based generative models for amortized Bayesian inference in regression and inverse PDE problems
Flow-ABI trains flow-matching models on historical data to produce a set-conditioned functional posterior sampler that delivers near-real-time Bayesian inference for regression and inverse PDE tasks without per-observation optimization.