Background: Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information ca...
Artem Lysenko, Michael Defoin-Platel, Keywan Hassa...
In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
—We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specif...
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
In this work, we investigate the viability of a novel combination of evoked responses as input signals for a general-purpose brain-machine interface (BMI). We demonstrate response...
Rudolph L. Mappus IV, Paul M. Corballis, Melody Mo...