This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Lidar waveforms are 1D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful ...
We propose gate level statistical simulation to bridge the gap between the most accurate Monte Carlo SPICE simulation and the most efficient circuit level statistical static timi...
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...