A variational Bayesian framework is employed in the paper for image segmentation using color clustering. A Gaussian mixture model is used to represent color distributions. Variati...
We analyze a previously unexplored generalization of the scalar total variation to vector-valued functions, which is motivated by geometric measure theory. A complete mathematical...
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
In this paper we propose two fast Total Variation (TV) based algorithms for image restoration by utilizing variational posterior distribution approximation. The unknown image and ...
Bruno Amizic, S. Derin Babacan, K. Michael Ng, Raf...
In this paper, we propose to combine Kazhdan’s FFT-based approach to surface reconstruction from oriented points with adaptive subdivision and partition of unity blending techni...
Oliver Schall, Alexander G. Belyaev, Hans-Peter Se...