130 citations · 671 across the 42 of their papers we have counts for
4 papers · 1 filter
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +7
The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in co…
Causality on Longitudinal Data: Stable Specification Search in Constrained Structural Equation Modeling
Ridho Rahmadi, Perry Groot, Marieke HC van Rijn +4
A typical problem in causal modeling is the instability of model structure learning, i.e., small changes in finite data can result in completely different optimal models. The prese…
Regularizing Solutions to the MEG Inverse Problem Using Space-Time Separable Covariance Functions
Arno Solin, Pasi Jylänki, Jaakko Kauramäki +3
In magnetoencephalography (MEG) the conventional approach to source reconstruction is to solve the underdetermined inverse problem independently over time and space. Here we presen…
The Artificial Mind's Eye: Resisting Adversarials for Convolutional Neural Networks using Internal Projection
Harm Berntsen, Wouter Kuijper, Tom Heskes
We introduce a novel artificial neural network architecture that integrates robustness to adversarial input in the network structure. The main idea of our approach is to force the…