activity
20122020
most citedTeichmüller extremal mapping and its applications to landmark matching registration

6 citations · 29 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2020★ 5 cited

Quasiconformal model with CNN features for large deformation image registration

Ho Law, Gary P. T. Choi, Ka Chun Lam +1

Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical mod…

cs.CL2020★ 2 cited

Mental representations of objects reflect the ways in which we interact with them

Ka Chun Lam, Francisco Pereira, Maryam Vaziri-Pashkam +2

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. When considering co…

cs.LG2020★ 1 cited

Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness

Patrick McClure, Dustin Moraczewski, Ka Chun Lam +2

Deep neural networks (DNNs) are being increasingly used to make predictions from functional magnetic resonance imaging (fMRI) data. However, they are widely seen as uninterpretable…

cs.CG2018★ 4 cited

Computing quasiconformal folds

Di Qiu, Ka-Chun Lam, Lok-Ming Lui

We propose a novel way of computing surface folding maps via solving a linear PDE. This framework is a generalization to the existing quasiconformal methods and allows manipulation…

math.NA2018★ 3 cited

A Fast Hierarchically Preconditioned Eigensolver Based On Multiresolution Matrix Decomposition

Thomas Y. Hou, De Huang, Ka Chun Lam +1

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 multireso…

math.NA2017

An adaptive fast solver for a general class of positive definite matrices via energy decomposition

Thomas Y. Hou, D. Huang, K. C. Lam +1

In this paper, we propose an adaptive fast solver for a general class of symmetric positive definite (SPD) matrices which include the well-known graph Laplacian. We achieve this by…