We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhib...
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
We propose a novel method for axonal bouton modeling and automated detection in populations of labeled neurons, as well as bouton distribution analysis for the study of neural cir...
Abhay Mavalankar, Amina Chebira, Christina A. Hall...
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...