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eess.SY2025
Approximating Analytically-Intractable Likelihood Densities with Deterministic Arithmetic for Optimal Particle Filtering
Orestis Kaparounakis, Yunqi Zhang, Phillip Stanley-Marbell
Particle filtering algorithms have enabled practical solutions to problems in autonomous robotics (self-driving cars, UAVs, warehouse robots), target tracking, and econometrics, wi…
eess.SP2025
Digital Methods to Quantify Sensor Output Uncertainty in Real Time
Orestis Kaparounakis, Phillip Stanley-Marbell
Modern data-driven applications that make real-time decisions increasingly depend on advanced sensors which use pre-stored calibration data. In such applications, accurate characte…