Research map / Probabilistic and scientific modeling / Dynamical systems
Identifying signal and noise structure in neural population activity with Gaussian process factor models
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add a noise latent component to the signal latents (ablation) | SNP-GPFA · Primate V1 held-out neuron log-likelihood | cross-validated log-likelihood | Helped |
| share at least two noise latents across V1 and AL instead of fully block-diagonal independent noise (ablation) | two-region SNP-GPFA · Multi-region rodent data | cross-validated log-likelihood | Helped |
| restrict Fourier coefficients via minimum length scale of 10 | Fourier BBVI · rodent and primate data | latent dimensionality of Fourier representation: 321 -> 44 | Helped |
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