We investigate generalizations of the allsubtrees "DOP" approach to unsupervised parsing. Unsupervised DOP models assign all possible binary trees to a set of sentences ...
This paper presents an algorithm for estimating the parameters of multicomponent chirp signals. The estimator is based on the cubic phase function (CPF), which is efficient to est...
Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then h...
Estimating divergence between two point processes, i.e. probability laws on the space of spike trains, is an essential tool in many computational neuroscience applications, such a...
This paper presents a novel probabilistic framework for 3D surface reconstruction from multiple stereo images. The method works on a discrete voxelized representation of the scene...