Hybrid neural network is a network with a combination of different artificial neural networks and approaches. It utilizes features of varying neural networks and approaches to achieve optimum results.
TreNet is a hybrid neural network used for trend prediction. It is composed of a long short term memory recurrent neural network (LSTM RNN) to capture dependency in historical trends, a convolutional neural network (CNN) to extract local features from local raw data and a feature fusion layer to merge and maximize features drawn from LSTM RNN and CNN.
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Fang Wan, Chaoyang Song
Logical Learning Through a Hybrid Neural Network with Auxiliary Inputs
Li Wan, Leo Zhu and Rob Fergus
A Hybrid Neural Network-Latent Topic Model
Tao Lin, Tian Guo and Karl Aberer
Hybrid Neural Networks for Learning the Trend in Time Series
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