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Existence Precedes Value: Joint Modeling of Observational Existence and Evolving States in Time Series Forecasting
Real-world time series are often highly incomplete and irregular due to sensor dormancy, transmission delays, and event-driven sampling, making reliable forecasting fundamentally challenging. Existing methods have evolved from impute-then-forecast pipelines to continuous-time models such as Neural O
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