How to implement maclaurin series in keras?
问题 I am trying to implement expandable CNN by using maclaurin series. The basic idea is the first input node can be decomposed into multiple nodes with different orders and coefficients. Decomposing single nodes to multiple ones can generate different non-linear line connection that generated by maclaurin series. Can anyone give me a possible idea of how to expand CNN with maclaurin series non-linear expansion? any thought? I cannot quite understand how to decompose the input node to multiple