16 citations · 45 across the 14 of their papers we have counts for
8 papers · 1 filter
Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence
Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang +1
This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics. We introduce a novel hybrid geometric deep learning-based model…
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
Yonghui Fan, Yalin Wang
Bayesian learning with Gaussian processes demonstrates encouraging regression and classification performances in solving computer vision tasks. However, Bayesian methods on 3D mani…
Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition
Gang Wang, Qunxi Dong, Jianfeng Wu +11
Cognitive decline due to Alzheimer's disease (AD) is closely associated with brain structure alterations captured by structural magnetic resonance imaging (sMRI). It supports the v…
Deep Representation Learning For Multimodal Brain Networks
Wen Zhang, Liang Zhan, Paul Thompson +1
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology…
Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML
Jie Zhang, Junting Zhang, Shalini Ghosh +4
Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community. The aim of lifelong…
MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression
Jie Zhang, Xiaolong Wang, Dawei Li +3
State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer. However, they pr…