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cs.NE2023
Episodic Memory Theory for the Mechanistic Interpretation of Recurrent Neural Networks
Arjun Karuvally, Peter Delmastro, Hava T. Siegelmann
Understanding the intricate operations of Recurrent Neural Networks (RNNs) mechanistically is pivotal for advancing their capabilities and applications. In this pursuit, we propose…
cs.LG2023
On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural Networks
Peter DelMastro, Rushiv Arora, Edward Rietman +1
Recurrent Neural Networks (RNNs) have shown great success in modeling time-dependent patterns, but there is limited research on their learned representations of latent temporal fea…