Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
In this paper, we present a novel algorithm for partial
intrinsic symmetry detection in 3D geometry. Unlike previous
work, our algorithm is based on a conceptually simple
and st...
Ruxandra Lasowski, Art Tevs, Hans-Peter Seidel, Mi...
In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes:...
We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the ...
Thomas A. Henzinger, Maria Mateescu, Linar Mikeev,...
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....