SYSTEMS AND METHODS FOR LEARNING AND PREDICTING TIME-SERIES DATA USING DEEP MULTIPLICATIVE NETWORKS

摘要

A method includes using a computational network (100) to learn and predict time- series data. The computational network includes one or more layers (102a, 102b, 102c), each having an encoder (104a, 104b, 104c) and a decoder (106a, 106b, 106c). The encoder of each layer multiplicatively combines (i) current feed-forward information from a lower layer or a computational network input (112) and (ii) past feedback information from a higher layer or that layer. The encoder of each layer generates current feed-forward information for the higher layer or that layer. The decoder of each layer multiplicatively combines (i) current feedback information from the higher layer or that layer and (ii) at least one of the current feed-forward information from the lower layer or the computational network input or past feed-forward information from the lower layer or the computational network input. The decoder of each layer generates current feedback information for the lower layer or a computational network output (114).