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Valerio Mante

2 accepted papers

2025

Mechanistic Interpretability of RNNs emulating Hidden Markov Models

NeurIPS 2025poster

Recurrent neural networks (RNNs) provide a powerful approach in neuroscience to infer latent dynamics in neural populations and to generate hypotheses about the neural computations underlying behavior. However, past work has focused on relatively simple, input-driven, and largely deterministic behav…

Cited by 0SourceScholar
2022

Operative dimensions in unconstrained connectivity of recurrent neural networks

NeurIPS 2022accept

Recurrent Neural Networks (RNN) are commonly used models to study neural computation. However, a comprehensive understanding of how dynamics in RNN emerge from the underlying connectivity is largely lacking. Previous work derived such an understanding for RNN fulfilling very specific constraints on…

Cited by 2SourcePDFScholar