<ul data-eligibleForWebStory="true"><li>The discussion revolves around the effects of partial observation in stochastic systems using the Koopman operator theory.</li><li>Data-driven algorithms based on the Koopman operator theory have shown progress in handling partial observations, aiming to connect with the Mori-Zwanzig formalism.</li><li>The importance of differentiating the state space and function space in stochastic systems is emphasized in the analysis.</li><li>Numerical experiments demonstrate the benefits of the delay embedding technique for partial observation in stochastic systems, revealing a power-law behavior in the accuracy of the additive noise amplitude.</li></ul>

Koopman operator-based discussion on partial observation in stochastic systems

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