13 citations · 50 across the 14 of their papers we have counts for
4 papers · 1 filter
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances
Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau +3
Deep neural networks (DNNs) have rapidly become a \textit{de facto} choice for medical image understanding tasks. However, DNNs are notoriously fragile to the class imbalance in im…
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again
Ajay Jaiswal, Peihao Wang, Tianlong Chen +3
Despite the enormous success of Graph Convolutional Networks (GCNs) in modeling graph-structured data, most of the current GCNs are shallow due to the notoriously challenging probl…
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model
Zhiyuan Mao, Ajay Jaiswal, Zhangyang Wang +1
Image restoration algorithms for atmospheric turbulence are known to be much more challenging to design than traditional ones such as blur or noise because the distortion caused by…
Training Your Sparse Neural Network Better with Any Mask
Ajay Jaiswal, Haoyu Ma, Tianlong Chen +2
Pruning large neural networks to create high-quality, independently trainable sparse masks, which can maintain similar performance to their dense counterparts, is very desirable du…