The Simple Rule Won Under Random Hazards

A two-action causal rule based on local nonlinearity decisively beat the corrected neural controller on fresh stochastic filtering rollouts.

ai-research, bayesian-filtering, nonlinear-filtering, robustness, heuristics

Useful Offline, Harmful Online

A bounded mixture state predicted much of an oracle’s value offline, yet repeated learned control shifted its own inputs and failed until a limited, partial correction.

ai-research, bayesian-filtering, nonlinear-filtering, imitation-learning, distribution-shift

The Oracle Could Choose, but the Online Planner Could Not

Exact-grid action values exposed a large information gap, while causal self-rollout became inaccurate and prohibitively expensive once planning work was counted.

ai-research, bayesian-filtering, nonlinear-filtering, online-planning, belief-compression

When Projection Choice Matters

An exact option-value model and scalar oracle experiments show when preserving a belief can reduce future loss—without yet producing a deployable controller.

ai-research, bayesian-filtering, nonlinear-filtering, decision-theory, belief-compression

Strict Online Variational Bayesian Filtering: What Survived The Stress Tests

A synthesis of strict online nonlinear filtering experiments: K2 FIVO bridge survived, while trajectories, couplings, flows, and predictive pressure exposed calibration failures.

ai-research, variational-filtering, nonlinear-filtering, particle-filtering, assumed-density-filtering, expectation-propagation

Strict Nonlinear Filtering With Mixtures, Particles, And Flows

A research note on turning Kalman-filter intuition into reference-free nonlinear filters with mixture beliefs, FIVO diagnostics, and scalar flows.

ai-research, variational-filtering, nonlinear-filtering, particle-filtering, normalizing-flows

Amortizing Quadrature Filters Without Losing Calibration

A strict mixture filter learned from deterministic Power-EP teachers improved some nonlinear alias cases, but exposed a hard alias-mass calibration tradeoff.

ai-research, variational-filtering, nonlinear-filtering, assumed-density-filtering, expectation-propagation

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.

ai-research, bayesian-filtering, variational-filtering, nonlinear-filtering, assumed-density-filtering

Reference-Free Quadrature Filters For The Sine Benchmark

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

ai-research, nonlinear-filtering, assumed-density-filtering, expectation-propagation

When Mixtures Beat Local ELBO In Nonlinear Filtering

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

ai-research, variational-filtering, nonlinear-filtering, iwae, particle-filtering

Example Research Note

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

ai-research, examples