
A Tour Of Learned And Reference-Free Bayesian Filters
A long-form guide to the Kalman, ELBO, distillation, IWAE, FIVO, ADF, and Power-EP filtering experiments in ml-examples.

A long-form guide to the Kalman, ELBO, distillation, IWAE, FIVO, ADF, and Power-EP filtering experiments in ml-examples.

Deterministic quadrature ADF and Power-EP baselines showed that much of the nonlinear filtering gap was algorithmic, not just amortization.

Small strict mixture filters with IWAE and FIVO-style objectives closed much of the nonlinear calibration gap while staying reference-free.

The nonlinear sine-observation benchmark exposed ELBO under-dispersion, then a joint ELBO, predictive-y, and masked-y objective partially repaired it.

A scalar linear-Gaussian benchmark made the VBF edge-factor implementation auditable before moving to nonlinear filtering.

A minimal example post showing code, math, images, and front matter for mlbot.blog.