1 code implementation • 27 Mar 2023 • Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker, Jiazhen Pan, Nil Stolt Ansó, Mark Mühlau, Jan S. Kirschke, Daniel Rueckert, Benedikt Wiestler
Clinical routine and retrospective cohorts commonly include multi-parametric Magnetic Resonance Imaging; however, they are mostly acquired in different anisotropic 2D views due to signal-to-noise-ratio and scan-time constraints.
no code implementations • 2 Jan 2020 • Nil Stolt Ansó
Large enough computed tomography (CT) data sets to train supervised deep models are often hard to come by.
no code implementations • 9 Oct 2019 • Nil Stolt Ansó
The Sampled Policy Gradient (SPG) algorithm is a new offline actor-critic variant that samples in the action space to approximate the policy gradient.
2 code implementations • 15 Sep 2018 • Anton Orell Wiehe, Nil Stolt Ansó, Madalina M. Drugan, Marco A. Wiering
In this paper, a new offline actor-critic learning algorithm is introduced: Sampled Policy Gradient (SPG).