24 citations · 41 across the 4 of their papers we have counts for
3 papers · 1 filter
Discrete flow posteriors for variational inference in discrete dynamical systems
Laurence Aitchison, Vincent Adam, Srinivas C. Turaga
Each training step for a variational autoencoder (VAE) requires us to sample from the approximate posterior, so we usually choose simple (e.g. factorised) approximate posteriors in…
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
Marcel Nonnenmacher, Srinivas C. Turaga, Jakob H. Macke
A powerful approach for understanding neural population dynamics is to extract low-dimensional trajectories from population recordings using dimensionality reduction methods. Curre…
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
Artur Speiser, Jinyao Yan, Evan Archer +3
Calcium imaging permits optical measurement of neural activity. Since intracellular calcium concentration is an indirect measurement of neural activity, computational tools are nec…