Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks

Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks

In this paper, we introduce a novel method to interpret recurrent neural networks (RNNs), particularly long short-term memory networks (LSTMs) at the cellular level. We propose a systematic pipeline for interpreting individual hidden state dynamics within the network using response characterization...

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Bibliographic Details
Main Authors: Hasani, Ramin, Amini, Alexander A, Lechner, Mathias, Naser, Felix M, Grosu, Radu, Rus, Daniela L
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
Online Access:https://hdl.handle.net/1721.1/130553

Internet

https://hdl.handle.net/1721.1/130553

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