Search Results for author:
Found 6 papers, 2 papers with code
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Psychiatry research seeks to understand the manifestations of psychopathology in behavior, as measured in questionnaire data, by identifying a small number of latent factors that explain them.
Understanding Mental Representations Of Objects Through Verbs Applied To Them
Finally, we show that the dimensions can be used to predict a state-of-the-art mental representation of objects, derived purely from human judgements of object similarity.
Quasiconformal model with CNN features for large deformation image registration
In this paper, we develop a novel method for large deformation image registration by a fusion of quasiconformal theory and convolutional neural network (CNN).
Mental representations of objects reflect the ways in which we interact with them
In order to interact with objects in our environment, humans rely on an understanding of the actions that can be performed on them, as well as their properties.
Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness
We introduce two quantitative evaluation procedures for saliency map methods in fMRI, applicable whenever a DNN or linear model is being trained to decode some information from imaging data.
A Fast Hierarchically Preconditioned Eigensolver Based On Multiresolution Matrix Decomposition
In this paper we propose a new iterative method to hierarchically compute a relatively large number of leftmost eigenpairs of a sparse symmetric positive matrix under the multiresolution operator compression framework.
