Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
We present the problem of estimating cortical connectivity between different regions of the cortex from scalp electroencephalographic (EEG) or magnetoencephalographic (MEG) data a...
—We consider distributed estimation of the inverse covariance matrix in Gaussian graphical models. These models factorize the multivariate distribution and allow for efficient d...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
A new method for estimating multivariate autoregressive (MVAR) models of cortical connectivity from surface EEG or MEG measurements is presented. Conventional approaches to this p...