According to the current standard model, neurons in lateral geniculate nucleus (LGN) operate linearly. There is, however, ample evidence that LGN responses are nonlinear. To accou...
A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
Pair approximations have often been used to predict equilibrium conditions in spatially-explicit epidemiological and ecological systems. In this work, we investigate whether this ...
This paper presents a novel algorithm for computing the relative motion between images from compressed linear measurements. We propose a geometry based correlation model that desc...