Mengjia Xu
Mengjia Xu
Assistant Professor, NJIT; CBMM, MIT; Applied Math, Brown University
Verified email at - Homepage
Cited by
Cited by
A deep convolutional neural network for classification of red blood cells in sickle cell anemia
M Xu, DP Papageorgiou, SZ Abidi, M Dao, H Zhao, GE Karniadakis
PLoS computational biology 13 (10), e1005746, 2017
Understanding graph embedding methods and their applications
M Xu
SIAM Review 63 (4), 825-853, 2021
Automated semantic segmentation of red blood cells for sickle cell disease
M Zhang, X Li, M Xu, Q Li
IEEE journal of biomedical and health informatics 24 (11), 3095-3102, 2020
Image region duplication detection based on circular window expansion and phase correlation
H Shao, T Yu, M Xu, W Cui
Forensic science international 222 (1-3), 71-82, 2012
Dynamics in Deep Classifiers trained with the Square Loss: normalization, low rank, neural collapse and generalization bounds
M Xu, A Rangamani, Q Liao, T Galanti, T Poggio
Research, 2023
Improved Hessian multiscale enhancement filter
J Yang, S Ma, Q Sun, W Tan, M Xu, N Chen, D Zhao
Bio-medical materials and engineering 24 (6), 3267-3275, 2014
RBC semantic segmentation for sickle cell disease based on deformable U-Net
M Zhang, X Li, M Xu, Q Li
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
A graph Gaussian embedding method for predicting Alzheimer's disease progression with MEG brain networks
M Xu, DL Sanz, P Garces, F Maestu, Q Li, D Pantazis
IEEE Transactions on Biomedical Engineering 68 (5), 1579-1588, 2021
Image segmentation and classification for sickle cell disease using deformable U-Net
M Zhang, X Li, M Xu, Q Li
arXiv preprint arXiv:1710.08149, 2017
Scalable algorithms for physics-informed neural and graph networks
K Shukla, M Xu, N Trask, GE Karniadakis
Data-Centric Engineering 3, e24, 2022
An image-enhancement method based on variable-order fractional differential operators
M Xu, J Yang, D Zhao, H Zhao
Bio-Medical Materials and Engineering 26 (s1), S1325-S1333, 2015
A new Graph Gaussian embedding method for analyzing the effects of cognitive training
M Xu, Z Wang, H Zhang, D Pantazis, H Wang, Q Li
PLoS computational biology 16 (9), e1008186, 2020
Multi-label detection and classification of red blood cells in microscopic images
W Qiu, J Guo, X Li, M Xu, M Zhang, N Guo, Q Li
2020 IEEE International Conference on Big Data (Big Data), 4257-4263, 2020
Generalization in deep network classifiers trained with the square loss
T Poggio, Q Liao, M Xu 112, 2020
AOSLO-net: a deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscopy images
Q Zhang, K Sampani, M Xu, S Cai, Y Deng, H Li, JK Sun, GE Karniadakis
Translational Vision Science & Technology 11 (8), 7-7, 2022
Dyng2g: An efficient stochastic graph embedding method for temporal graphs
M Xu, AV Singh, GE Karniadakis
IEEE Transactions on Neural Networks and Learning Systems, 2022
Automatic MRI brain tissue extraction algorithm based on three-dimensional gray-scale transformation model
J Yang, W Tan, S Ma, Q Sun, M Xu, N Chen, D Zhao
Journal of medical imaging and health informatics 4 (6), 907-911, 2014
Norm-based Generalization Bounds for Sparse Neural Networks
T Galanti, M Xu, L Galanti, T Poggio
Advances in Neural Information Processing Systems 36, 2024
Hyperbolic graph embedding of MEG brain networks to study brain alterations in individuals with subjective cognitive decline
C Baker, I Suárez-Méndez, G Smith, EB Marsh, M Funke, JC Mosher, ...
bioRxiv, 2023
Gaussian embedding-based functional brain connectomic analysis for amnestic mild cognitive impairment patients with cognitive training
M Xu, Z Wang, H Zhang, D Pantazis, H Wang, Q Li
bioRxiv, 779744, 2019
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