[HTML][HTML] Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg… - Neurons, behavior, data …, 2023 - ncbi.nlm.nih.gov
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

Expressive architectures enhance interpretability of dynamics-based neural population models.

AR Sedler, C Versteeg… - Neurons, Behavior, Data …, 2023 - europepmc.org
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg, C Pandarinath - arXiv preprint arXiv:2212.03771, 2022 - arxiv.org
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg… - … behavior, data analysis …, 2023 - pubmed.ncbi.nlm.nih.gov
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg, C Pandarinath - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg… - Neurons, Behavior, Data …, 2023 - nbdt.scholasticahq.com
Artificial neural networks that can recover latent dynamics from recorded neural activity may
provide a powerful avenue for identifying and interpreting the dynamical motifs underlying …

[引用][C] Expressive architectures enhance interpretability of dynamics-based neural population models

AR Sedler, C Versteeg… - Neurons …, 2023 - The neurons, behavior, data …