109 citations · 130 across the 4 of their papers we have counts for
12 papers
Chronic, cortex-wide imaging of specific cell populations during behavior
Joao Couto, Simon Musall, Xiaonan R Sun +8
Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes like attention, decision-making, and act…
A zero-inflated gamma model for deconvolved calcium imaging traces
Xue-Xin Wei, Ding Zhou, Andres Grosmark +6
Calcium imaging is a critical tool for measuring the activity of large neural populations. Much effort has been devoted to developing "pre-processing" tools for calcium video data,…
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
Ding Zhou, Yuanjun Gao, Liam Paninski
The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learnin…
Neural Clustering Processes
Ari Pakman, Yueqi Wang, Catalin Mitelut +2
Probabilistic clustering models (or equivalently, mixture models) are basic building blocks in countless statistical models and involve latent random variables over discrete spaces…
Amortized Bayesian inference for clustering models
Ari Pakman, Liam Paninski
We develop methods for efficient amortized approximate Bayesian inference over posterior distributions of probabilistic clustering models, such as Dirichlet process mixture models.…
Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data
Daniel Hernandez, Antonio Khalil Moretti, Ziqiang Wei +3
Latent variable models have been widely applied for the analysis of time series resulting from experimental neuroscience techniques. In these datasets, observations are relatively…