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Causal Temporal Graph Convolutional Neural Networks (CTGCN)
Our CTGCN architecture is based on a causal discovery mechanism, and is capable of discovering the underlying causal processes.
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting
In order to quickly track changes in the model and put more weight on recent data, the RLS filter uses a forgetting factor which exponentially weights down observations by the order of their arrival.
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