In this chapter, we present Motion Assisted Steering Kernel (MASK) regression, a novel multi-frame approach for interpolating video data spatially, temporally, or spatiotemporally, and for video noise reduction, including compression artifact removal. The MASK method takes both local spatial orientations and local motion vectors into account and adaptively constructs a suitable filter at every ...

Einstein-Podolsky-Rosen (EPR) steering describes the ability of one observer to nonlocally "steer" the other observer's state through local measurements. EPR steering exhibits a unique asymmetric property; i.e., the steerability can differ between observers, which can lead to one-way EPR steering in which only one observer obtains steerability in the steering process. This property is inherentl...

The assembly of functional neural circuits in the developing brain requires neurons to extend axons to the correct targets. This in turn requires the navigating tips of axons to respond appropriately to guidance cues present along the axonal pathway, despite being cellular 'outposts' far from the soma. Work over the past few years has demonstrated a critical role for local translation within th...

I will described a nonparametric framework for locally adaptive signal processing and analysis. This framework is based upon the notion of Kernel Regression which we generalize to adapt to local characteristics of the given data, resulting in descriptors which take into account both the spatial density of the samples (”the geometry”), and the actual values of those samples (”the radiometry”). T...