Junxiang Chen

According to our database, Junxiang Chen authored at least 30 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improvement of motor imagery electroencephalogram decoding by iterative weighted Sparse-Group Lasso.

Bin Lu, Fuwang Wang, Shiwei Wang, Junxiang Chen, Guilin Wen, Rongrong Fu

Expert Syst. Appl., March, 2024

DrasCLR: A self-supervised framework of learning disease-related and anatomy-specific representation for 3D lung CT images.

Ke Yu, Li Sun, Junxiang Chen, Maxwell Reynolds, Tigmanshu Chaudhary, Kayhan Batmanghelich

Medical Image Anal., February, 2024

Two-mobile anchor node-based localization in wireless sensor networks.

Weiwei Hu, Junxiang Chen, Shenying Yang

J. Ambient Intell. Humaniz. Comput., January, 2024

Manifold attention-enhanced multi-domain convolutional network for decoding motor imagery intention.

Bin Lu, Xiaodong Huang, Junxiang Chen, Rongrong Fu, Guilin Wen

Knowl. Based Syst., 2024

EEG emotion recognition using EEG-SWTNS neural network through EEG spectral image.

Mengpu Cai, Junxiang Chen, Chengcheng Hua, Guilin Wen, Rongrong Fu

Inf. Sci., 2024

Research on High-Precision Control of Hydraulic Excavator Based on Optimal Trajectory Planning.

Junxiang Chen, Kelong Xu, Xiangdong Kong, Yujie Guo, Chao Ai

IEEE Access, 2024

2023

Transforming Complex Problems Into K-Means Solutions.

Hongfu Liu, Junxiang Chen, Jennifer G. Dy, Yun Fu

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Automatic Representative Frame Selection and Intrathoracic Lymph Node Diagnosis With Endobronchial Ultrasound Elastography Videos.

Mingxing Xu, Junxiang Chen, Jin Li, Xinxin Zhi, Wenrui Dai, Jiayuan Sun, Hongkai Xiong

IEEE J. Biomed. Health Informatics, 2023

DrasCLR: A Self-supervised Framework of Learning Disease-related and Anatomy-specific Representation for 3D Medical Images.

Ke Yu, Li Sun, Junxiang Chen, Maxwell Reynolds, Tigmanshu Chaudhary, Kayhan Batmanghelich

CoRR, 2023

Text Readability of Smartphone in Dark Mode: Effects of Font Type, Font Weight and Color.

Junxiang Chen, Pengyu Zhu, Jing Yun, Baixuan Tian, Yalan Yang, Na Liu

Proceedings of the Human Aspects of IT for the Aged Population, 2023

2022

Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis.

Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich

IEEE J. Biomed. Health Informatics, 2022

Web table data integration based on smart campus scenarios to resolve name disambiguation of scientific research personnel.

Junfan Jin, Junxiang Chen, Jilin Zhang, Tao Li, Ruixiang Qian, Feng Liu, Li Zhou, Yongjian Ren

Proceedings of the 46th IEEE Annual Computers, Software, and Applications Conferenc, 2022

2021

Recognizing single-trial motor imagery EEG based on interpretable clustering method.

Rongrong Fu, Weishuai Li, Junxiang Chen, Mengmeng Han

Biomed. Signal Process. Control., 2021

Extracting Disease-Relevant Features with Adversarial Regularization.

Junxiang Chen, Li Sun, Ke Yu, Kayhan Batmanghelich

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020

Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN.

Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich

CoRR, 2020

Twitter discussions and concerns about COVID-19 pandemic: Twitter data analysis using a machine learning approach.

Jia Xue, Junxiang Chen, Ran Hu, Chen Chen, ChengDa Zheng, Tingshao Zhu

CoRR, 2020

Machine learning on Big Data from Twitter to understand public reactions to COVID-19.

Jia Xue, Junxiang Chen, Chen Chen, ChengDa Zheng, Tingshao Zhu

CoRR, 2020

Explanation by Progressive Exaggeration.

Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich

Proceedings of the 8th International Conference on Learning Representations, 2020

Generative-Discriminative Complementary Learning.

Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Weakly Supervised Disentanglement by Pairwise Similarities.

Junxiang Chen, Kayhan Batmanghelich

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Robust Ordinal VAE: Employing Noisy Pairwise Comparisons for Disentanglement.

Junxiang Chen, Kayhan Batmanghelich

CoRR, 2019

Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data - An Application to Climate Prediction.

Yumin Liu, Junxiang Chen, Auroop R. Ganguly, Jennifer G. Dy

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Crowdclustering with Partition Labels.

Junxiang Chen, Yale Chang, Peter J. Castaldi, Michael H. Cho, Brian Hobbs, Jennifer G. Dy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

A Bayesian Nonparametric Model for Disease Subtyping: Application to Emphysema Phenotypes.

James C. Ross, Peter J. Castaldi, Michael H. Cho, Junxiang Chen, Yale Chang, Jennifer G. Dy, Edwin K. Silverman, George R. Washko, Raúl San José Estépar

IEEE Trans. Medical Imaging, 2017

Clustering with Domain-Specific Usefulness Scores.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Multiple Clustering Views from Multiple Uncertain Experts.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 34th International Conference on Machine Learning, 2017

Clustering from Multiple Uncertain Experts.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

A Generative Block-Diagonal Model for Clustering.

Junxiang Chen, Jennifer G. Dy

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Interpretable Clustering via Discriminative Rectangle Mixture Model.

Junxiang Chen, Yale Chang, Brian Hobbs, Peter J. Castaldi, Michael H. Cho, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model.

Junxiang Chen, Wei Dai, Yizhou Sun, Jennifer G. Dy

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015