Traffic signals analysis using qSDiff and qHDiff with surrogate data. - Mengjia Xu; Pengjian Shang; Jianan Xia (Commun. Nonlinear Sci. Numer. Simul., 2015)

Modified generalized sample entropy and surrogate data analysis for stock markets. - Mengjia Xu; Pengjian Shang; Jingjing Huang (Commun. Nonlinear Sci. Numer. Simul., 2016)

Image Segmentation and Classification for Sickle Cell Disease using Deformable U-Net. - Mo Zhang; Xiang Li 001; Mengjia Xu; Quanzheng Li (CoRR, 2017)

A deep convolutional neural network for classification of red blood cells in sickle cell anemia. - Mengjia Xu; Dimitrios P. Papageorgiou; Sabia Z. Abidi; Ming Dao; Hong Zhao; George E. Karniadakis (PLoS Comput. Biol., 2017)

Dynamic Changes of the Alpine Wetlands in Tibet, China. - Dong Liu; Mengjia Xu (IGARSS, 2018)

RBC Semantic Segmentation for Sickle Cell Disease Based on Deformable U-Net. - Mo Zhang; Xiang Li 001; Mengjia Xu; Quanzheng Li (MICCAI (4), 2018)

Present Vertical Crustal Movement in North Segment Of North-South Tectonic Belt Derived From GNSS. - Jing Wang; Mengjia Xu; Heqing Ma; Shiyang Liu; Xinyan Li (IGARSS, 2019)

NPP-Based Evaluation of Ecological Assets in China's Ecological Conservation Redline Area. - Mengjia Xu; Yan Wang; Changxin Zou; Dong Liu (IGARSS, 2019)

Multi-label Detection and Classification of Red Blood Cells in Microscopic Images. - Wei Qiu; Jiaming Guo; Xiang Li 001; Mengjia Xu; Mo Zhang; Ning Guo; Quanzheng Li (IEEE BigData, 2020)

A new Graph Gaussian embedding method for analyzing the effects of cognitive training. - Mengjia Xu; Zhijiang Wang; Haifeng Zhang; Dimitrios Pantazis; Huali Wang; Quanzheng Li (PLoS Comput. Biol., 2020)

Automated Semantic Segmentation of Red Blood Cells for Sickle Cell Disease. - Mo Zhang; Xiang Li 001; Mengjia Xu; Quanzheng Li (IEEE J. Biomed. Health Informatics, 2020)

AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images. - Qian Zhang; Konstantina Sampani; Mengjia Xu; Shengze Cai; Yixiang Deng; He Li; Jennifer K. Sun; George Em Karniadakis (CoRR, 2021)

Understanding Graph Embedding Methods and Their Applications. - Mengjia Xu (SIAM Rev., 2021)

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks. - Mengjia Xu; David López-Sanz; Pilar Garcés; Fernando Maestú; Quanzheng Li; Dimitrios Pantazis (IEEE Trans. Biomed. Eng., 2021)

Scalable algorithms for physics-informed neural and graph networks. - Khemraj Shukla; Mengjia Xu; Nathaniel Trask; George Em Karniadakis (CoRR, 2022)

Norm-based Generalization Bounds for Sparse Neural Networks. - Tomer Galanti; Mengjia Xu; Liane Galanti; Tomaso A. Poggio (NeurIPS, 2023)

Norm-based Generalization Bounds for Compositionally Sparse Neural Networks. - Tomer Galanti; Mengjia Xu; Liane Galanti; Tomaso A. Poggio (CoRR, 2023)

Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning. - Luca Candelori; Alexander G. Abanov; Jeffrey Berger; Cameron J. Hogan; Vahagn Kirakosyan; Kharen Musaelian; Ryan Samson; James E. T. Smith; Dario Villani; Martin T. Wells; Mengjia Xu (CoRR, 2024)

A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers. - Ashish Parmanand Pandey; Alan John Varghese; Sarang Patil; Mengjia Xu (CoRR, 2024)

TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers. - Alan John Varghese; Aniruddha Bora; Mengjia Xu; George Em Karniadakis (Neural Networks, 2024)

DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs. - Mengjia Xu; Apoorva Vikram Singh; George Em Karniadakis (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hierarchical contrastive learning and color standardization for single image sand-dust removal. - Yazhong Si; Mengjia Xu; Fan Yang (Pattern Anal. Appl., 2024)

Hyperbolic Graph Embedding of MEG Brain Networks to Study Brain Alterations in Individuals With Subjective Cognitive Decline. - Cole Baker; Isabel Suárez-Méndez; Grace Smith; Elisabeth B. Marsh; Michael Funke; John C. Mosher; Fernando Maestú; Mengjia Xu; Dimitrios Pantazis (IEEE J. Biomed. Health Informatics, 2024)

Hierarchical Mamba Meets Hyperbolic Geometry: A New Paradigm for Structured Language Embeddings. - Sarang Patil; Ashish Parmanand Pandey; Ioannis Koutis; Mengjia Xu (CoRR, 2025)

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability. - Giuseppe Di Caro; Vahagn Kirakosyan; Alexander G. Abanov; Luca Candelori; Nadine Hartmann; Ernest T. Lam; Kharen Musaelian; Ryan Samson; Dario Villani; Martin T. Wells; Richard J. Wenstrup; Mengjia Xu (CoRR, 2025)

Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories. - Hugo Ramirez; Davide Tabarelli; Arianna Brancaccio; Paolo Belardinelli; Elisabeth B. Marsh; Michael Funke; John C. Mosher; Fernando Maestú; Mengjia Xu; Dimitrios Pantazis (IEEE J. Biomed. Health Informatics, 2025)

Quantum Geometry of Data. - Alexander G. Abanov; Luca Candelori; Harold C. Steinacker; Martin T. Wells; Jerome R. Busemeyer; Cameron J. Hogan; Vahagn Kirakosyan; Nicola Marzari; Sunil Pinnamaneni; Dario Villani; Mengjia Xu; Kharen Musaelian (CoRR, 2025)

BrainATCL: Adaptive Temporal Brain Connectivity Learning for Functional Link Prediction and Age Estimation. - Yiran Huang; Amirhossein Nouranizadeh; Christine Ahrends; Mengjia Xu (CoRR, 2025)

Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning. - Lin Song; Xingwei Wu; Mengjia Xu; Ling Xue; Xun Yu; Zongqi Cheng; Chenrong Huang; Liyan Miao (BMC Medical Informatics Decis. Mak., 2025)