Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model
Fig 2
Training OSLMM on neural data scales well with the number of latent functions.
The running time per iteration with different number of latent functions for the Stochastic Linear Mixing Model (SLMM), the Orthogonal Stochatic Linear Mixing Model (OSLMM), and the Stochastic Gaussian Process Regression Network (SGPRN).