Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where m...
Modeling the variability of brain structures is a fundamental problem in the neurosciences. In this paper, we start from a dataset of precisely delineated anatomical structures in ...
Pierre Fillard, Vincent Arsigny, Xavier Pennec, Pa...
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...