We present a novel method for procedurally modeling large complex shapes. Our approach is general-purpose and takes as input any 3D polyhedral model provided by a user. The algori...
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
Log-linear models have recently been used in acoustic modeling for speech recognition systems. This has been motivated by competitive results compared to systems based on Gaussian...
Causality is a central issue in many AI applications. Social causality, in contrast to physical causality, seeks to attribute cause and responsibility to social events, and account...
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...