3 papers
cs.LG2026
Amortized Factor Inference Networks for Posterior Inference
Joohwan Ko, Justin Domke
Amortized inference promises fast test-time Bayesian inference, but existing methods are inherently tied to fixed models. Extending amortization to unseen models typically requires…
cs.LG2025
Model-Informed Flows for Bayesian Inference
Joohwan Ko, Justin Domke
Variational inference often struggles with the posterior geometry exhibited by complex hierarchical Bayesian models. Recent advances in flow-based variational families and Variatio…
cs.LG2025
Large Language Bayes
Justin Domke
Many domain experts do not have the time or expertise to write formal Bayesian models. This paper takes an informal problem description as input, and combines a large language mode…