18 citations · 31 across the 5 of their papers we have counts for
5 papers
Nest-DGIL: Nesterov-optimized Deep Geometric Incremental Learning for CS Image Reconstruction
Xiaohong Fan, Yin Yang, Ke Chen +2
Proximal gradient-based optimization is one of the most common strategies to solve inverse problem of images, and it is easy to implement. However, these techniques often generate…
Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model
Hongrun Zhang, Liam Burrows, Yanda Meng +5
Image segmentation is a fundamental task in the field of imaging and vision. Supervised deep learning for segmentation has achieved unparalleled success when sufficient training da…
An Interpretable MRI Reconstruction Network with Two-grid-cycle Correction and Geometric Prior Distillation
Xiaohong Fan, Yin Yang, Ke Chen +2
Although existing deep learning compressed-sensing-based Magnetic Resonance Imaging (CS-MRI) methods have achieved considerably impressive performance, explainability and generaliz…
Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza, Yixuan Li
Out-of-distribution (OOD) detection is important for deploying machine learning models in the real world, where test data from shifted distributions can naturally arise. While a pl…
Weak solutions of the three-dimensional hypoviscous elastodynamics with finite kinetic energy
Ke Chen, Jie Liu
We construct weak solutions to the 3D hypoviscous incompressible elastodynamics with finite kinetic energy which was unknown in literatures. Our result holds for fractional hypovis…