We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
Many graphics applications represent deformable surfaces through dynamic meshes. To be consistent during deformations, the dynamic meshes require an adaptation process. In this pa...
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementat...
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
Abstract Sensor devices produce data that are unreliable, low-level, and seldom able to be used directly by applications. In this paper, we propose Metaphysical Data Independence (...
Shawn R. Jeffery, Michael J. Franklin, Minos N. Ga...