32 citations · 125 across the 23 of their papers we have counts for
26 papers
CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations
Chengfeng Wu, Tao Zou, Yanru Wu +1
Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, existing optimization-centric…
Learning What is Worth Learning: Active and Sequential Domain Adaptation for Multi-modal Gross Tumor Volume Segmentation
Jingyun Yang, Guoqing Zhang, Jingge Wang +1
Accurate gross tumor volume segmentation on multi-modal medical data is critical for radiotherapy planning in nasopharyngeal carcinoma and glioblastoma. Recent advances in deep neu…
Understanding Knowledge Transferability for Transfer Learning: A Survey
Haohua Wang, Jingge Wang, Zijie Zhao +9
Transfer learning has become an essential paradigm in artificial intelligence, enabling the transfer of knowledge from a source task to improve performance on a target task. This a…
TMT: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation
Enming Zhang, Zhengyu Li, Yanru Wu +5
Recent advances in Vision Transformers (ViTs) have significantly advanced semantic segmentation performance. However, their adaptation to new target domains remains challenged by d…
Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
Jingyun Yang, Guoqing Zhang, Jingge Wang +1
Recent advances in foundation models have brought promising results in computer vision, including medical image segmentation. Fine-tuning foundation models on specific low-resource…
CCIS-Diff: A Generative Model with Stable Diffusion Prior for Controlled Colonoscopy Image Synthesis
Yifan Xie, Jingge Wang, Tao Feng +2
Colonoscopy is crucial for identifying adenomatous polyps and preventing colorectal cancer. However, developing robust models for polyp detection is challenging by the limited size…
Selecting the Best Sequential Transfer Path for Medical Image Segmentation with Limited Labeled Data
Jingyun Yang, Jingge Wang, Guoqing Zhang +1
The medical image processing field often encounters the critical issue of scarce annotated data. Transfer learning has emerged as a solution, yet how to select an adequate source t…
Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum
Hanbing Liu, Jingge Wang, Xuan Zhang +2
Addressing the large distribution gap between training and testing data has long been a challenge in machine learning, giving rise to fields such as transfer learning and domain ad…
Artificial Intelligence-based Motion Tracking in Cancer Radiotherapy: A Review
Elahheh Salari, Jing Wang, Jacob Wynne +2
Radiotherapy aims to deliver a prescribed dose to the tumor while sparing neighboring organs at risk (OARs). Increasingly complex treatment techniques such as volumetric modulated…
NeutralUniverseMachine: An Empirical Model for the Evolution of HI and H Gas in the Universe
Hong Guo, Jing Wang, Michael G. Jones +1
Accurately modeling the cold gas content in the universe is challenging for current theoretical models. We propose a new empirical model NeutralUniverseMachine for the evolution of…
Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy
Shoieb Ahmed Chowdhury, M. F. N. Taufique, Jing Wang +5
Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in mic…
Denoising Magnetic Resonance Spectroscopy (MRS) Data Using Stacked Autoencoder for Improving Signal-to-Noise Ratio and Speed of MRS
Jing Wang, Bing Ji, Yang Lei +3
Background: Magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) w…
Augmenting Pathologists with NaviPath: Design and Evaluation of a Human-AI Collaborative Navigation System
Hongyan Gu, Chunxu Yang, Mohammad Haeri +7
Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing…
Effects of Active Galactic Nucleus Feedback on Cold Gas Depletion and Quenching of Central Galaxies
Wenlin Ma, Kexin Liu, Hong Guo +5
We investigate the influence of active galactic nucleus (AGN) feedback on the galaxy cold gas content and its connection to galaxy quenching in three hydrodynamical simulations of…
MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering
Shanshan Song, Jiangyun Li, Jing Wang +2
There is a key problem in the medical visual question answering task that how to effectively realize the feature fusion of language and medical images with limited datasets. In ord…
Replicating Persistent Memory Key-Value Stores with Efficient RDMA Abstraction
Qing Wang, Youyou Lu, Jing Wang +1
Combining persistent memory (PM) with RDMA is a promising approach to performant replicated distributed key-value stores (KVSs). However, existing replication approaches do not wor…
Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge
Jingge Wang, Liyan Xie, Yao Xie +2
Domain generalization aims at learning a universal model that performs well on unseen target domains, incorporating knowledge from multiple source domains. In this research, we con…
Cold Gas Reservoirs of Low- and High-mass Central Galaxies Differ in Response to Active Galactic Nucleus Feedback
Hong Guo, Michael G. Jones, Jing Wang
The growth of supermassive black holes, especially the associated state of active galactic nuclei (AGNs), is generally believed to be the key step in regulating star formation in m…
Class-conditioned Domain Generalization via Wasserstein Distributional Robust Optimization
Jingge Wang, Yang Li, Liyan Xie +1
Given multiple source domains, domain generalization aims at learning a universal model that performs well on any unseen but related target domain. In this work, we focus on the do…
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions
Jing Wang, Anna Choromanska
This paper addresses the problem of optimizing partition functions in a stochastic learning setting. We propose a stochastic variant of the bound majorization algorithm that relies…
Information-Based Model Discrimination for Digital Twin Behavioral Matching
Jairo Viola, YangQuan Chen, Jing Wang
Digital Twin is a breaking technology that allows creating virtual representations of complex physical systems based on updated information of the system and its physical laws. How…
DHash: Enabling Dynamic and Efficient Hash Tables
Junchang Wang, Xiong Fu, Fu Xiao +1
Given a specified average load factor, hash tables offer the appeal of constant time lookup operations. However, hash tables could face severe hash collisions because of malicious…
Dendrite Net: A White-Box Module for Classification, Regression, and System Identification
Gang Liu, Jing Wang
The simulation of biological dendrite computations is vital for the development of artificial intelligence (AI). This paper presents a basic machine learning algorithm, named Dendr…
The GWAC Data Processing and Management System
Yang Xu, Liping Xin, Xuhui Han +10
GWAC will have been built an integrated FOV of 5,000 and have already built 1,800 square . The limit magnitude of a 10-second exposure image in the moonless ni…