647 citations · 1.7k across the 29 of their papers we have counts for
4 papers · 1 filter
Bayesian spike inference from calcium imaging data
Eftychios A. Pnevmatikakis, Josh Merel, Ari Pakman +1
We present efficient Bayesian methods for extracting neuronal spiking information from calcium imaging data. The goal of our methods is to sample from the posterior distribution of…
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions
Ari Pakman, Liam Paninski
We present a new approach to sample from generic binary distributions, based on an exact Hamiltonian Monte Carlo algorithm applied to a piecewise continuous augmentation of the bin…
A shotgun sampling solution for the common input problem in neural connectivity inference
Daniel Soudry, Suraj Keshri, Patrick Stinson +3
Inferring connectivity in neuronal networks remains a key challenge in statistical neuroscience. The `common input' problem presents the major roadblock: it is difficult to reliabl…
Fast inference in generalized linear models via expected log-likelihoods
Alexandro D. Ramirez, Liam Paninski
Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can gre…