Memming Park, Jonathan Pillow and I recently had our workshop proposal, Scalable Models for high-dimensional neural data, accepted to be part of the Computational and Systems Neuroscience (Cosyne) conference, which takes place in February 2014. You can check out the workshop site for more information.
We’ve just uploaded the first code release of the Pitman-Yor Mixture (PYM) entropy estimator to GitHub. This is code from our recent NIPS paper “Bayesian estimation of discrete entropy with mixtures of stick-breaking priors“. You can find more details in a longer manuscript which recently appeared on the arXiv.
Two of my abstracts (together with Memming Park and Jonathan Pillow) were accepted to this year’s Computational and Systems Neuroscience (Cosyne) conference! In “Got a moment or two? Neural models and linear dimensionality reduction,” we propose an extension of the Generalized Linear Model (GLM) framework which integrates well-known methods for neural dimensionality reduction with a parametric model of neural responses. In “Semi-parametric Bayesian entropy estimation for binary spike trains,” we extend the work of our recent NIPS paper by using a simple model of spike counts as the “base measure” for a Dirichlet distribution.