Step-wise refinement is a powerful paradigm for developing a complex program from a simple program by adding features incrementally. We present the AHEAD (Algebraic Hierarchical Eq...
Don S. Batory, Jacob Neal Sarvela, Axel Rauschmaye...
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
Adaptive mesh refinement (AMR) is a numerical simulation technique used in computational fluid dynamics (CFD). By using a set of nested grids of different resolutions, AMR combine...
Gunther H. Weber, Oliver Kreylos, Terry J. Ligocki...
This paper studies a hierarchical Bayesian model for nonlinear hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are polynomial functions of li...
Yoann Altmann, Abderrahim Halimi, Nicolas Dobigeon...
The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...