In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
We present a de novo hierarchical simulation framework for first-principles based predictive simulations of materials and their validation on high-end parallel supercomputers and ...
Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, ...
Abstract: A hybrid quantum mechanical/molecular mechanical (QM/MM) potential energy function with HartreeFock, density functional theory (DFT), and post-HF (RIMP2, MP2, CCSD) capab...
H. Lee Woodcock III, Milan Hodoscek, Andrew T. B. ...