13 citations · 50 across the 14 of their papers we have counts for
14 papers
Physics-Driven Turbulence Image Restoration with Stochastic Refinement
Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan +1
Image distortion by atmospheric turbulence is a stochastic degradation, which is a critical problem in long-range optical imaging systems. A number of research has been conducted d…
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt +17
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance. This paper presents the end-to…
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
Ajay Jaiswal, Shiwei Liu, Tianlong Chen +1
Large pre-trained transformers are show-stealer in modern-day deep learning, and it becomes crucial to comprehend the parsimonious patterns that exist within them as they grow in s…
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation
Wenqing Zheng, S P Sharan, Ajay Kumar Jaiswal +4
For a complicated algorithm, its implementation by a human programmer usually starts with outlining a rough control flow followed by iterative enrichments, eventually yielding care…
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Shiwei Liu, Tianlong Chen, Zhenyu Zhang +4
Sparse Neural Networks (SNNs) have received voluminous attention predominantly due to growing computational and memory footprints of consistently exploding parameter count in large…
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers
Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal +2
Despite their remarkable achievement, gigantic transformers encounter significant drawbacks, including exorbitant computational and memory footprints during training, as well as se…
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…
RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification
Ajay Jaiswal, Liyan Tang, Meheli Ghosh +3
Radiology reports are unstructured and contain the imaging findings and corresponding diagnoses transcribed by radiologists which include clinical facts and negated and/or uncertai…
SCALP -- Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata
Ajay Jaiswal, Tianhao Li, Cyprian Zander +4
Computer-aided diagnosis plays a salient role in more accessible and accurate cardiopulmonary diseases classification and localization on chest radiography. Millions of people get…
Spending Your Winning Lottery Better After Drawing It
Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen +2
Lottery Ticket Hypothesis (LTH) suggests that a dense neural network contains a sparse sub-network that can match the performance of the original dense network when trained in isol…
Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays
Yan Han, Chongyan Chen, Liyan Tang +7
Chest X-ray becomes one of the most common medical diagnoses due to its noninvasiveness. The number of chest X-ray images has skyrocketed, but reading chest X-rays still have been…