1 code implementation • 26 May 2023 • Kai Zhang, Jun Yu, Zhiling Yan, Yixin Liu, Eashan Adhikarla, Sunyang Fu, Xun Chen, Chen Chen, Yuyin Zhou, Xiang Li, Lifang He, Brian D. Davison, Quanzheng Li, Yong Chen, Hongfang Liu, Lichao Sun
In this paper, we introduce a unified and generalist Biomedical Generative Pre-trained Transformer (BiomedGPT) model, which leverages self-supervision on large and diverse datasets to accept multi-modal inputs and perform a range of downstream tasks.
no code implementations • 10 May 2023 • Suraj Rajendran, Weishen Pan, Mert R. Sabuncu, Yong Chen, Jiayu Zhou, Fei Wang
By offering a more comprehensive approach to healthcare data integration, patchwork learning has the potential to revolutionize the clinical applicability of ML models.
no code implementations • 17 Apr 2023 • Rui Liu, Bin Yin, Ziyi Cao, Qianchen Xia, Yong Chen, Dell Zhang
Personalized news recommender systems help users quickly find content of their interests from the sea of information.
no code implementations • 20 Mar 2023 • Guoliang Wang, Yanlei Shang, Yong Chen
A critical challenge to image-text retrieval is how to learn accurate correspondences between images and texts.
no code implementations • 1 Mar 2023 • Siqi Li, Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Chuan Hong, Feng Xie, Han Yuan, Mingxuan Liu, Daniel M. Buckland, Yong Chen, Nan Liu
We also calculated the average AUC values and SDs for each local model, and the FedScore model showed promising accuracy and stability with a high average AUC value which was closest to the one of the pooled model and SD which was lower than that of most local models.
no code implementations • 11 Jan 2023 • Shiping Wang, Zhihao Wu, Yuhong Chen, Yong Chen
Graph convolutional networks (GCNs) have been attracting widespread attentions due to their encouraging performance and powerful generalizations.
no code implementations • 27 Dec 2022 • Wang Qi, Rui Liu, Yuan Zuo, Yong Chen, Dell Zhang
Creating an essay based on a few given topics is a challenging NLP task.
no code implementations • 27 Dec 2022 • Chaoqi Zhen, Yanlei Shang, Xiangyu Liu, Yifei Li, Yong Chen, Dell Zhang
Natural Language Processing (NLP) has been revolutionized by the use of Pre-trained Language Models (PLMs) such as BERT.
no code implementations • 31 Aug 2022 • Jingyi Duan, Yang Ning, Xi Chen, Yong Chen
In many scenarios such as genome-wide association studies where dependences between variables commonly exist, it is often of interest to infer the interaction effects in the model.
no code implementations • 17 Feb 2022 • Yi Nian, Xinyue Hu, Rui Zhang, Jingna Feng, Jingcheng Du, Fang Li, Yong Chen, Cui Tao
The 1, 672, 110 filtered triples were used to train with knowledge graph completion algorithms (i. e., TransE, DistMult, and ComplEx) to predict candidates that might be helpful for AD treatment or prevention.
no code implementations • 28 Sep 2021 • Wentao Li, Jiayi Tong, Md. Monowar Anjum, Noman Mohammed, Yong Chen, Xiaoqian Jiang
Objectives: This paper develops two algorithms to achieve federated generalized linear mixed effect models (GLMM), and compares the developed model's outcomes with each other, as well as that from the standard R package (`lme4').
1 code implementation • 31 Jul 2021 • Zhaoming Kong, Lichao Sun, Hao Peng, Liang Zhan, Yong Chen, Lifang He
In this paper, we propose MGNet, a simple and effective multiplex graph convolutional network (GCN) model for multimodal brain network analysis.
no code implementations • 16 Jul 2021 • Yilin Liu, Yong Chen, Pew-Thian Yap
Magnetic resonance Fingerprinting (MRF) is a relatively new multi-parametric quantitative imaging method that involves a two-step process: (i) reconstructing a series of time frames from highly-undersampled non-Cartesian spiral k-space data and (ii) pattern matching using the time frames to infer tissue properties (e. g., T1 and T2 relaxation times).
2 code implementations • 12 May 2021 • Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel Marcus, Mikhail Milchenko, Arash Nazer, Hassan Fathallah-Shaykh, Roland Wiest, Andras Jakab, Marc-Andre Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern Menze, Klaus Maier-Hein, Spyridon Bakas
The goals of the FeTS challenge are directly represented by the two included tasks: 1) the identification of the optimal weight aggregation approach towards the training of a consensus model that has gained knowledge via federated learning from multiple geographically distinct institutions, while their data are always retained within each institution, and 2) the federated evaluation of the generalizability of brain tumor segmentation models "in the wild", i. e. on data from institutional distributions that were not part of the training datasets.
no code implementations • 4 May 2021 • Sicong Che, Hao Peng, Lichao Sun, Yong Chen, Lifang He
This paper aims to provide a generic Federated Multi-View Learning (FedMV) framework for multi-view data leakage prevention, which is based on different types of local data availability and enables to accommodate two types of problems: Vertical Federated Multi-View Learning (V-FedMV) and Horizontal Federated Multi-View Learning (H-FedMV).
no code implementations • 21 Jan 2021 • Juncai Pu, Jun Li, Yong Chen
On the bases of the improved method, the effects for different numbers of initial points sampled, residual collocation points sampled, network layers, neurons per hidden layer on the second order genuine rational soliton solution dynamics of the DNLS are considered, and the relevant analysis when the locally adaptive activation function chooses different initial values of scalable parameters are also exhibited in the simulation of the two-order rogue wave solution.
Pattern Formation and Solitons Exactly Solvable and Integrable Systems
no code implementations • 5 Jan 2021 • Martijn J. Schuemie, Yong Chen, David Madigan, Marc A. Suchard
Studies of the effects of medical interventions increasingly take place in distributed research settings using data from multiple clinical data sources including electronic health records and administrative claims.
no code implementations • 6 Nov 2020 • Yong Chen, Zhi-Gang Jia, Ya-Xin Peng, Yan Peng
In this way, compared with conventional QSVD, the proposed watermarking strategy avoids more modifications to a single color image layer and a better visual quality of the watermarked image is observed.
no code implementations • 11 Aug 2020 • Yongchao Liu, Yue Jin, Yong Chen, Teng Teng, Hang Ou, Rui Zhao, Yao Zhang
Accelerating deep model training and inference is crucial in practice.
no code implementations • 24 Jun 2020 • Yong Chen, Lu Wang, Jiajia Hu, Mingbin Ye
Fall event detection, as one of the greatest risks to the elderly, has been a hot research issue in the solitary scene in recent years.
no code implementations • 6 Jan 2020 • Wei He, Yong Chen, Naoto Yokoya, Chao Li, Qibin Zhao
In this paper, we propose a new model, named coupled tensor ring factorization (CTRF), for HSR.
no code implementations • 24 Nov 2019 • Haipeng Xing, Yingru Wu, Yong Chen, Michael Zhang
Background: The nucleus of eukaryotic cells spatially packages chromosomes into a hierarchical and distinct segregation that plays critical roles in maintaining transcription regulation.
no code implementations • 1 Nov 2019 • Yifei Wang, Rui Liu, Yong Chen, Hui Zhangs, Zhiwen Ye
Spectral Clustering is a popular technique to split data points into groups, especially for complex datasets.
no code implementations • 16 Sep 2019 • Sisheng Liang, Zhou Yang, Fang Jin, Yong Chen
Efficient job scheduling on data centers under heterogeneous complexity is crucial but challenging since it involves the allocation of multi-dimensional resources over time and space.
no code implementations • 6 Jul 2019 • Jingcheng Du, Chongliang Luo, Qiang Wei, Yong Chen, Cui Tao
In this study, we proposed a convolutional neural network model for gender prediction using English Twitter text as input.
1 code implementation • 5 Mar 2019 • Ray Bai, Gemma E. Moran, Joseph Antonelli, Yong Chen, Mary R. Boland
We introduce the spike-and-slab group lasso (SSGL) for Bayesian estimation and variable selection in linear regression with grouped variables.
no code implementations • 18 Oct 2018 • Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang
In many real-world applications, data are often unlabeled and comprised of different representations/views which often provide information complementary to each other.
no code implementations • 11 Sep 2018 • Yong Chen, Ming Zhou, Ying Wen, Yaodong Yang, Yufeng Su, Wei-Nan Zhang, Dell Zhang, Jun Wang, Han Liu
Deep Q-learning has achieved a significant success in single-agent decision making tasks.
no code implementations • Scientia Marina 2016 • Jintao Wang, Wei Yu, Xinjun Chen, Yong Chen
Because this squid has a short lifespan and is an ecological opportunist, the dynamics of its stock is greatly influenced by the environmental conditions, which need to be considered in its assessment and management.