Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...
Chris Bailey-Kellogg, Sheetal Chainraj, Gopal Pand...
This work presents a real-time, data-parallel approach for global label assignment on regular grids. The labels are selected according to a Markov random field energy with a Potts...
Christopher Zach, David Gallup, Jan-Michael Frahm,...
Surface triangle meshes and volume data are two commonly used representations of digital geometry. Converting from triangle meshes to volume data is challenging, since triangle mes...
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....