Dynamic Online Processor-Native Inference for State Estimation

arXiv:2607.12095 · eess.SP, cs.LG, stat.ML · Submitted 2026-07-13 · Read on arXiv

Orestis Kaparounakis

eess.SP, cs.LG, stat.ML

Submitted: 2026-07-13

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 123× in this paper · explained in 2 episodes
• Accuracy — 62× in this paper · explained in 1 episode
• Trace — 32× in this paper · explained in 2 episodes
• Wasserstein Distance — 24× in this paper · explained in 6 episodes
• Pareto Frontier — 18× in this paper · explained in 2 episodes
• Fidelity — 12× in this paper · explained in 2 episodes
• Bayesian Inference — 10× in this paper · explained in 6 episodes
• Configuration Space — 5× in this paper · explained in 2 episodes
• Uncertainty Propagation — 5× in this paper · explained in 4 episodes
• Benchmarking — 4× in this paper · explained in 4 episodes
• Calibration — 3× in this paper · explained in 9 episodes
• Elias — 2× in this paper · explained in 2 episodes
• Monte Carlo Sampling — 2× in this paper · explained in 2 episodes
• Quantization — 2× in this paper · explained in 15 episodes
• Structural Constraints — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Ornstein–Uhlenbeck Process — 1× in this paper · explained in 3 episodes

Sources

• Quantization of Probability Distributions via Divide-and-Conquer: Convergence and Error Propagation under Distributional Arithmetic Operations

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