27 citations · 58 across the 28 of their papers we have counts for
8 papers · 1 filter
Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging
Xinyu Peng, Ziyang Zheng, Wenrui Dai +5
Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with significantly fewer k-space measur…
scBiGNN: Bilevel Graph Representation Learning for Cell Type Classification from Single-cell RNA Sequencing Data
Rui Yang, Wenrui Dai, Chenglin Li +3
Single-cell RNA sequencing (scRNA-seq) technology provides high-throughput gene expression data to study the cellular heterogeneity and dynamics of complex organisms. Graph neural…
LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning
Mingxing Xu, Wenrui Dai, Chenglin Li +2
Graph pooling has been increasingly considered for graph neural networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods commonly co…
Graph Neural Networks With Lifting-based Adaptive Graph Wavelets
Mingxing Xu, Wenrui Dai, Chenglin Li +3
Spectral-based graph neural networks (SGNNs) have been attracting increasing attention in graph representation learning. However, existing SGNNs are limited in implementing graph f…
Message Passing in Graph Convolution Networks via Adaptive Filter Banks
Xing Gao, Wenrui Dai, Chenglin Li +3
Graph convolution networks, like message passing graph convolution networks (MPGCNs), have been a powerful tool in representation learning of networked data. However, when data is…
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification
Rui Yang, Wenrui Dai, Chenglin Li +2
Message passing has evolved as an effective tool for designing Graph Neural Networks (GNNs). However, most existing methods for message passing simply sum or average all the neighb…
MimicNorm: Weight Mean and Last BN Layer Mimic the Dynamic of Batch Normalization
Wen Fei, Wenrui Dai, Chenglin Li +2
Substantial experiments have validated the success of Batch Normalization (BN) Layer in benefiting convergence and generalization. However, BN requires extra memory and float-point…
Graph Pooling with Node Proximity for Hierarchical Representation Learning
Xing Gao, Wenrui Dai, Chenglin Li +2
Graph neural networks have attracted wide attentions to enable representation learning of graph data in recent works. In complement to graph convolution operators, graph pooling is…