6 citations · 7 across the 9 of their papers we have counts for
10 papers
Adaptive Coordinate Transforms for Neural Operators
Chaoyu Liu, Zhonghao Li, Gaohang Chen +5
Neural operators have achieved promising performance on partial differential equations (PDEs), but most existing models are built on fixed Eulerian coordinates. This mismatch betwe…
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Adaptive Correction for Ensuring Conservation Laws in Neural Operators
Chaoyu Liu, Yangming Li, Zhongying Deng +2
Physical laws, such as the conversation of mass and momentum, are fundamental principles in many physical systems. Neural operators have achieved promising performance in learning…
Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis
Zhongying Deng, Haoyu Wang, Ziyan Huang +6
Brain diseases, such as Alzheimer's disease and brain tumors, present profound challenges due to their complexity and societal impact. Recent advancements in brain foundation model…
D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction
Lipei Zhang, Rui Sun, Zhongying Deng +3
Variations in Magnetic resonance imaging (MRI) scanners and acquisition protocols cause distribution shifts that degrade reconstruction performance on unseen data. Test-time adapta…
Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey
Amer Essakine, Yanqi Cheng, Chun-Wun Cheng +5
Implicit Neural Representations (INRs) have emerged as a paradigm in knowledge representation, offering exceptional flexibility and performance across a diverse range of applicatio…
Bilevel Hypergraph Networks for Multi-Modal Alzheimer's Diagnosis
Angelica I. Aviles-Rivero, Chun-Wun Cheng, Zhongying Deng +2
Early detection of Alzheimer's disease's precursor stages is imperative for significantly enhancing patient outcomes and quality of life. This challenge is tackled through a semi-s…
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
Andrey Bryutkin, Jiahao Huang, Zhongying Deng +3
We present a novel graph transformer framework, HAMLET, designed to address the challenges in solving partial differential equations (PDEs) using neural networks. The framework use…
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios
Lihao Liu, Yanqi Cheng, Zhongying Deng +6
Multi-object tracking in traffic videos is a crucial research area, offering immense potential for enhancing traffic monitoring accuracy and promoting road safety measures through…
HIBMatch: Hypergraph Information Bottleneck for Semi-supervised Alzheimer's Progression
Zhongying Deng, Shujun Wang, Angelica I Aviles-Rivero +2
Alzheimer's disease progression prediction is critical for patients with early Mild Cognitive Impairment (MCI) to enable timely intervention and improve their quality of life. Whil…