Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems

Autor: Herzberg, William, Rowe, Daniel B., Hauptmann, Andreas, Hamilton, Sarah J.

The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains, such as pixelated images. If the underlying model is solved on nonuniform meshes, arising from a finite element method typical f

Externí odkaz: http://arxiv.org/abs/2103.15138

Transient Overexpression of Striatal D2 Receptors Impairs Operant Motivation and Interval Timing.

Autor: Drew, Michael R., Simpson, Eleanor H., Kellendonk, Christoph, Herzberg, William G., Lipatova, Olga, Fairhurst, Stephen, Kandel, Eric R., Malapani, Chara, Balsam, Peter D.

Publikováno v: Journal of Neuroscience; 7/18/2007, Vol. 27 Issue 29, p7731-7739, 9p, 1 Color Photograph, 1 Black and White Photograph, 7 Graphs

Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems.

Autor: Herzberg W; Department of Mathematical and Statistical Sciences; Marquette University, Milwaukee, WI 53233 USA., Rowe DB; Department of Mathematical and Statistical Sciences; Marquette University, Milwaukee, WI 53233 USA., Hauptmann A; Research Unit of Mathematical Sciences; University of Oulu, Oulu, Finland and with the Department of Computer Science; University College London, London, United Kingdom., Hamilton SJ; Department of Mathematical and Statistical Sciences; Marquette University, Milwaukee, WI 53233 USA.

Publikováno v: IEEE transactions on computational imaging [IEEE Trans Comput Imaging] 2021; Vol. 7, pp. 1341-1353. Date of Electronic Publication: 2021 Dec 02.