64 citations · 154 across the 12 of their papers we have counts for
12 papers
On Disentangled Training for Nonlinear Transform in Learned Image Compression
Han Li, Shaohui Li, Wenrui Dai +5
Learned image compression (LIC) has demonstrated superior rate-distortion (R-D) performance compared to traditional codecs, but is challenged by training inefficiency that could in…
Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling
Mingxing Xu, Chenglin Li, Wenrui Dai +4
Pooling and unpooling are two essential operations in constructing hierarchical spherical convolutional neural networks (HS-CNNs) for comprehensive feature learning in the spherica…
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
Ziyang Zheng, Wenrui Dai, Duoduo Xue +3
It is promising to solve linear inverse problems by unfolding iterative algorithms (e.g., iterative shrinkage thresholding algorithm (ISTA)) as deep neural networks (DNNs) with lea…
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…
Optimization-based Block Coordinate Gradient Coding
Qi Wang, Ying Cui, Chenglin Li +2
Existing gradient coding schemes introduce identical redundancy across the coordinates of gradients and hence cannot fully utilize the computation results from partial stragglers.…
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…