lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems

Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional neural activity for downstream applications in science and engineering.

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Andrew R. Sedler, Chethan Pandarinath (2024). Dataset: lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems. https://doi.org/10.57702/p5143m9c

DOI retrieved: December 2, 2024

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Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2309.01230
Author Andrew R. Sedler
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Chethan Pandarinath
Homepage https://github.com/arsedler9/lfads-torch