27 citations · 28 across the 4 of their papers we have counts for
5 papers
Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry
Duoduo Xue, Zhiyu Zhu, Junhui Hou
Image generative models aim to sample data points from the underlying data manifold, a task that requires learning and decoding a dense, low-dimensional, and compact parameterizati…
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…
Point Cloud Denoising With Fine-Granularity Dynamic Graph Convolutional Networks
Wenqiang Xu, Wenrui Dai, Duoduo Xue +4
Due to limitations in acquisition equipment, noise perturbations often corrupt 3-D point clouds, hindering down-stream tasks such as surface reconstruction, rendering, and further…
Point Cloud Resampling with Learnable Heat Diffusion
Wenqiang Xu, Wenrui Dai, Duoduo Xue +4
Generative diffusion models have shown empirical successes in point cloud resampling, generating a denser and more uniform distribution of points from sparse or noisy 3D point clou…
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…