Learning to Bias: Machine Learning-Enhanced Particle Filters

arXiv:2609.30498 · cs.LG, stat.ML · Submitted 2026-09-24 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Benchmark — 60× in this paper · explained in 2 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Optimal Particle Filter — 7× in this paper
• Degeneracy — 6× in this paper · explained in 3 episodes
• Neural Optimal Particle Filter — 6× in this paper
• Auxiliary Particle Filter — 5× in this paper
• Data Assimilation — 5× in this paper · explained in 2 episodes
• Sample Efficiency — 4× in this paper · explained in 4 episodes
• Sequential Importance Sampling — 4× in this paper
• Calibration — 3× in this paper · explained in 7 episodes
• Core — 3× in this paper · explained in 2 episodes
• Inner-Sampling Proposal Filter — 3× in this paper
• Normalizing Flow — 3× in this paper · explained in 3 episodes
• Normalizing Flows — 3× in this paper · explained in 4 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Unscented Particle Filter — 3× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• Computational overhead — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Mean Absolute Deviation Error — 2× in this paper
• Neural Adaptive Sequential Monte Carlo — 2× in this paper
• Unscented Kalman Filter — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Sequential Monte Carlo (SMC) — 1× in this paper · explained in 2 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes

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