Search Results for author:
Found 3 papers, 1 papers with code
Bayesian Deep Net GLM and GLMM
Efficient computational methods for high-dimensional Bayesian inference are developed using Gaussian variational approximation, with a parsimonious but flexible factor parametrization of the covariance matrix.
Computation
Automatic Face Aging in Videos via Deep Reinforcement Learning
This paper presents a novel approach to synthesize automatically age-progressed facial images in video sequences using Deep Reinforcement Learning.
Predicting Lattice Phonon Vibrational Frequencies Using Deep Graph Neural Networks
Our work demonstrates the capability of deep graph neural networks to learn to predict phonon spectrum properties of crystal structures in addition to phonon density of states (DOS) and electronic DOS in which the output dimension is constant.
