Gradient-based filters achieve exponential stability independent of the data-generating process and MSE bounds under mild moments, with implicit filters needing weaker conditions than explicit ones.
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Develops MRSS model with latent states to capture dynamic health status and time-varying treatment effects in multi-modal digital phenotype data from Parkinson's patients.
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Gradient-based filtering under misspecification: Stability and error bounds
Gradient-based filters achieve exponential stability independent of the data-generating process and MSE bounds under mild moments, with implicit filters needing weaker conditions than explicit ones.
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Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes
Develops MRSS model with latent states to capture dynamic health status and time-varying treatment effects in multi-modal digital phenotype data from Parkinson's patients.