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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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Cite this as

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

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Additional Info

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