167 citations · 424 across the 41 of their papers we have counts for
7 papers · 1 filter
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications
Xinlei Zhou, Han Liu, Farhad Pourpanah +2
Quantifying the uncertainty of supervised learning models plays an important role in making more reliable predictions. Epistemic uncertainty, which usually is due to insufficient k…
A Systematic Survey of Deep Learning-based Single-Image Super-Resolution
Juncheng Li, Zehua Pei, Wenjie Li +4
Single-image super-resolution (SISR) is an important task in image processing, which aims to enhance the resolution of imaging systems. Recently, SISR has made a huge leap and has…
Structure-Preserving Deraining with Residue Channel Prior Guidance
Qiaosi Yi, Juncheng Li, Qinyan Dai +3
Single image deraining is important for many high-level computer vision tasks since the rain streaks can severely degrade the visibility of images, thereby affecting the recognitio…
Transformer for Single Image Super-Resolution
Zhisheng Lu, Juncheng Li, Hong Liu +3
Single image super-resolution (SISR) has witnessed great strides with the development of deep learning. However, most existing studies focus on building more complex networks with…
Finite Difference Nets: A Deep Recurrent Framework for Solving Evolution PDEs
Cheng Chang, Liu Liu, Tieyong Zeng
There has been an arising trend of adopting deep learning methods to study partial differential equations (PDEs). In this paper, we introduce a deep recurrent framework for solving…
Rank-One Prior: Toward Real-Time Scene Recovery
Jun Liu, Ryan Wen Liu, Jianing Sun +1
Scene recovery is a fundamental imaging task for several practical applications, e.g., video surveillance and autonomous vehicles, etc. To improve visual quality under different we…
A deep neural network approach on solving the linear transport model under diffusive scaling
Liu Liu, Tieyong Zeng, Zecheng Zhang
In this work, we propose a learning method for solving the linear transport equation under the diffusive scaling. Due to the multiscale nature of our model equation, the model is c…