Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space

ArXi:2510.12916v2 Announce Type: replace-cross Systems of interacting continuous-time Marko chains are a powerful model class, but inference is typically intractable in high dimensional settings. Auxiliary information, such as noisy observations, is typically only available at discrete times, and incorporating it via a Doob's $h$-transform gives rise to an intractable posterior process that requires approximation. We