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Found 2 papers, 1 papers with code
Neural Additive Models for Nowcasting
By employing generalized additive models, the proposed NAM-NC successfully explains each input value's importance for multiple variables and time steps.
Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided Embedding
TGNet learns an autoregressive model, conditioned on temporal contexts of forecasting targets from temporal-guided embedding.
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