This paper investigates the role of existing "probabilistic" schemes to reason about various everyday situations on the basis of data from multiple heterogeneous physical...
The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to ...
Michael A. Arbib, Aude Billard, Marco Iacoboni, Er...
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Models of human control strategy (HCS), which accurately emulate dynamic human behavior, have far reaching potential in areas ranging from robotics to virtual reality to the intel...