Loc Tran

According to our database, Loc Tran authored at least 21 papers between 2011 and 2022.

Collaborative distances:

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

2022

Metacells untangle large and complex single-cell transcriptome networks.

Mariia Bilous, Loc Tran, Chiara Cianciaruso, Aurélie Gabriel, Hugo Michel, Santiago J. Carmona, Mikael J. Pittet, David Gfeller

BMC Bioinform., December, 2022

DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation.

Vy Bui, Li-Yueh Hsu, Lin-Ching Chang, An-Yu Sun, Loc Tran, Sujata M. Shanbhag, Wunan Zhou, Nehal N. Mehta, Marcus Y. Chen

Frontiers Artif. Intell., 2022

Integrating Quaternion Graph Convolutional Networks with Tucker Decomposition for Link Prediction on Knowledge Graphs.

Thanh Le, Chi Tran, Loc Tran, Bac Le

Proceedings of the Knowledge Science, Engineering and Management, 2022

A Novel Integrating Approach Between Graph Neural Network and Complex Representation for Link Prediction in Knowledge Graph.

Thanh Le, Loc Tran, Bac Le

Proceedings of the Recent Challenges in Intelligent Information and Database Systems, 2022

2021

Noise-robust classification with hypergraph neural network.

Nguyen Trinh Vu Dang, Loc Tran, Linh Tran

CoRR, 2021

2020

Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset.

Vy Bui, Li-Yueh Hsu, Sujata M. Shanbhag, Loc Tran, W. Patricia Bandettini, Lin-Ching Chang, Marcus Y. Chen

Comput. Biol. Medicine, 2020

2019

To Detect Irregular Trade Behaviors In Stock Market By Using Graph Based Ranking Methods.

Loc Tran, Linh Tran

CoRR, 2019

Solve fraud detection problem by using graph based learning methods.

Loc Tran, Tuan Tran, Linh Tran, An Mai

CoRR, 2019

K-Segments Under Bagging approach: An experimental Study on Extremely Imbalanced Data Classification.

Tuan Tran, Loc Tran, An Mai

Proceedings of the 19th International Symposium on Communications and Information Technologies, 2019

2015

A Robust Deep Model for Improved Classification of AD/MCI Patients.

Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li

IEEE J. Biomed. Health Informatics, 2015

A comparative study of two prediction models for brain tumor progression.

Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li

Proceedings of the Image Processing: Algorithms and Systems XIII, 2015

Adaptive graph construction for Isomap manifold learning.

Loc Tran, Zezhong Zheng, Guoqing Zhou, Jiang Li

Proceedings of the Image Processing: Algorithms and Systems XIII, 2015

2014

High Dimensional Data Set Analysis Using a Large-Scale Manifold Learning Approach.

Loc Tran

PhD thesis, 2014

Robust Deep Learning for Improved Classification of AD/MCI Patients.

Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li

Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

2013

High-dimensional MRI data analysis using a large-scale manifold learning approach.

Loc Tran, Debrup Banerjee, Jihong Wang, Ashok J. Kumar, Frederic D. McKenzie, Yaohang Li, Jiang Li

Mach. Vis. Appl., 2013

Large-Scale Manifold Learning Using an Adaptive Sparse Neighbor Selection Approach for Brain Tumor Progression Prediction.

Loc Tran, Frederic D. McKenzie, Jihong Wang, Jiang Li

Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013

The Un-normalized Graph p-Laplacian Based Semi-supervised Learning Method and Protein Function Prediction Problem.

Loc Tran

Proceedings of the Knowledge and Systems Engineering, 2013

2012

Hypergraph and protein function prediction with gene expression data

Loc Tran

CoRR, 2012

Application of three graph Laplacian based semi-supervised learning methods to protein function prediction problem

Loc Tran

CoRR, 2012

2011

A Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction.

Loc Tran, Debrup Banerjee, Xiaoyan Sun, Jihong Wang, Ashok J. Kumar, David Vinning, Frederic D. McKenzie, Yaohang Li, Jiang Li

Proceedings of the Machine Learning in Medical Imaging - Second International Workshop, 2011

Prediction of brain tumor progression using multiple histogram matched MRI scans.

Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic D. McKenzie, Jihong Wang

Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011