Relevance of model parameters

[francescomalandrino]

Is there a way to get the relevance of model parameters, in addition to the inputs (and intermediate results) thereof?

The PLOS paper ("On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation") mentions per-neuron relevance conservation, hence, I assume it would make sense to keep track of the incoming (or outgoing) relevance of each neuron (and, more generally, each DNN parameter), and make that accessible to the users of the library.

Does that make sense? Thanks!