Latent linear dynamical systems with Bernoulli observations provide a
po...
Active learning seeks to reduce the number of samples required to estima...
Approximate Bayesian inference methods provide a powerful suite of tools...
An open question in systems and computational neuroscience is how neural...
Gaussian Process Factor Analysis (GPFA) has been broadly applied to the
...
Different neural networks trained on the same dataset often learn simila...
In many problem settings, parameter vectors are not merely sparse, but
d...
An exciting branch of machine learning research focuses on methods for
l...
Neural circuits contain heterogeneous groups of neurons that differ in t...