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 (Author), Amini, Alexander A (Author), Lechner, Mathias (Author), Naser, Felix M (Author), Grosu, Radu (Author), Rus, Daniela L (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-05-04T14:56:09Z.
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