We studied the dynamics of a neural network which have both of recurrent excitatory and random inhibitory connections. Neurons started to become active when a relatively weak trans...
While sophisticated neural networks and graphical models have been developed for predicting conditional probabilities in a non-stationary environment, major improvements in the tr...
Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
—The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function represen...