Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
A multiple fundamental frequency estimator is presented in this work. At each time frame, a set of fundamental frequencies is found in a frame by frame analysis taking into accoun...
Spatial image processing chips, known as silicon retinas, are based on the architecture of vertebrate retina and can be mathematically represented as the Laplacian of Gaussian (LO...
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...