LFADS, or Latent Factor Analysis via Dynamical Systems, is a deep learning method to infer latent dynamics from single-trial neural spiking data. LFADS uses a nonlinear dynamical system (a recurrent neural network) to infer the dynamics underlying observed population activity and to extract ‘denoised’ single-trial firing rates from neural spiking data. Read the LFADS manuscript, published at Nature Methods, or the LFADS pre-print for more details. https://www.biorxiv.org/content/10.1101/152884v1