State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
We address the consensus-based distributed linear filtering problem, where a discrete time, linear stochastic process is observed by a network of sensors. We assume that the consen...
— Shape is one of the useful information for object detection. The human visual system can often recognize objects based on the 2-D outline shape alone. In this paper, we address...
In this paper, we propose a new method that can consistently orient all normals of any mesh (if at all possible), while ensuring that most polygons are seen with their front-faces...
We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity...