Probabilistic Circuits for Irregular Multivariate Time Series Forecasting
CircuITS is a new architecture for forecasting irregular multivariate time series using probabilistic circuits. It uses a recursive Sum-Product Network structure to model complex joint distributions while structurally guaranteeing marginalization consistency, ensuring predictions for any subset of variables are valid. This approach achieves superior density estimation compared to existing methods.