1 code implementation • 12 Dec 2023 • Ka Chun Lam, Bridget W Mahony, Armin Raznahan, Francisco Pereira
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.
no code implementations • 1 Jan 2021 • Ka Chun Lam, Francisco Pereira, Maryam Vaziri-Pashkam, Kristin Woodard, Emalie McMahon
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.
no code implementations • 30 Oct 2020 • Ho Law, Gary P. T. Choi, Ka Chun Lam, Lok Ming Lui
In this paper, we develop a novel method for large deformation image registration by a fusion of quasiconformal theory and convolutional neural network (CNN).
no code implementations • 22 Jun 2020 • Ka Chun Lam, Francisco Pereira, Maryam Vaziri-Pashkam, Kristin Woodard, Emalie McMahon
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.
1 code implementation • 23 Apr 2020 • Patrick McClure, Dustin Moraczewski, Ka Chun Lam, Adam Thomas, Francisco Pereira
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.
no code implementations • 10 Apr 2018 • Thomas Y. Hou, De Huang, Ka Chun Lam, Ziyun Zhang
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.