arxivcs.LGcs.AIcs.MAeess.SY2026-06-26
Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter
George Stamatelis, Kyriakos Stylianopoulos, George C. Alexandropoulos
Online latent state estimation constitutes a fundamental challenge within the artificial intelligence field, serving as a foundational tool for diverse applications, including sequential decision making, anomaly and change-point detection. In this paper, a novel online distribute…