This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
Abstract – In this paper, we propose a modeling approach for the average power consumption of macro-blocks that are typically used in digital signal processing (DSP) systems, suc...
This paper presents statistical default logic, an expansion of classical (i.e., Reiter) default logic that allows us to model common inference patterns found in standard inferenti...
Abstract. Recently we have proposed Gaussian mixtures as a local statistical model to synthesize artificial textures. We describe the statistical dependence of pixels of a movable ...
Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
Jonathan Pillow, Liam Paninski, Eero P. Simoncelli