State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
Although mature technologies exist for acquiring images, geometry, and normals of small objects, they remain cumbersome and time-consuming for non-experts to employ on a large sca...
Benedict J. Brown, Corey Toler-Franklin, Diego Neh...
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
■ The antisaccade task has proven highly useful in basic and clinical neuroscience, and the neural structures involved are well documented. However, the specific neurocognitive ...
Benedikt Reuter, Christian Kaufmann, Julia Bender,...
—The use of passive optical networks (PONs) enables access rates of multi-Gbit/sec bandwidth and provision of quality of service for high definition multimedia services. In this...
Yan Wang, Moshe Zukerman, Ron Addie, Sammy Chan, R...