We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is diff...
Insights from human perception of moving faces have the potential to provide interesting insights for technical animation systems as well as in the neural encoding of facial expre...
We describe a prototype software system for investigating novel human-computer interaction techniques for 3-D geospatial data. This system, M4-Geo (Multi-Modal Mesh Manipulation o...
Background: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene ex...
Samir B. Amin, Parantu K. Shah, Aimin Yan, Sophia ...