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2020 – today
- 2025
[j56]Yue Yang, Kaixian Yu, Shan Gao, Sheng Yu, Di Xiong, Chuanyang Qin, Huiyuan Chen
, Jiarui Tang, Niansheng Tang, Hongtu Zhu:
Alzheimer's disease knowledge graph enhances knowledge discovery and disease prediction. Comput. Biol. Medicine 192: 110285 (2025)- [j55]Xiaochuan Wang, Yuqi Fang, Qianqian Wang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection. Medical Image Anal. 101: 103403 (2025) - [j54]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Disentangled latent energy-based style translation: An image-level structural MRI harmonization framework. Neural Networks 184: 107039 (2025) - [c64]Shuguang Yu, Wenqian Xu, Xinyi Zhou, Xuechun Wang, Hongtu Zhu, Fan Zhou:
Enhancing Prediction Performance through Influence Measure. ICLR 2025 - [c63]Yongheng Sun, Yueh Z. Lee, Genevieve A. Woodard, Hongtu Zhu, Chunfeng Lian, Mingxia Liu:
R2Gen-Mamba: A Selective State Space Model for Radiology Report Generation. ISBI 2025: 1-4 - [i41]Wei Ruan, Yanjun Lyu, Jing Zhang, Jiazhang Cai, Peng Shu, Yang Ge, Yao Lu, Shang Gao, Yue Wang, Peilong Wang, Lin Zhao, Tao Wang, Yufang Liu, Luyang Fang, Ziyu Liu, Zhengliang Liu, Yiwei Li, Zihao Wu, Junhao Chen, Hanqi Jiang, Yi Pan, Zhenyuan Yang, Jingyuan Chen, Shizhe Liang, Wei Zhang, Terry Ma, Yuan Dou, Jianli Zhang, Xinyu Gong, Qi Gan, Yusong Zou, Zebang Chen, Yuanxin Qian, Shuo Yu, Jin Lu, Kenan Song, Xianqiao Wang, Andrea Sikora, Gang Li, Xiang Li, Quanzheng Li, Yingfeng Wang, Lu Zhang, Yohannes Abate, Lifang He, Wenxuan Zhong, Rongjie Liu, Chao Huang, Wei Liu, Ye Shen, Ping Ma, Hongtu Zhu, Yajun Yan, Dajiang Zhu, Tianming Liu:
Large Language Models for Bioinformatics. CoRR abs/2501.06271 (2025) - [i40]Peng Huang, Shu Hu, Bo Peng, Jiashu Zhang, Hongtu Zhu, Xi Wu, Xin Wang:
Diffusion-empowered AutoPrompt MedSAM. CoRR abs/2502.06817 (2025) - [i39]Siwei Han, Peng Xia, Ruiyi Zhang, Tong Sun, Yun Li, Hongtu Zhu, Huaxiu Yao:
MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding. CoRR abs/2503.13964 (2025) - [i38]Run Yang, Runpeng Dai, Siran Gao, Xiaocheng Tang, Fan Zhou, Hongtu Zhu:
Spatio-temporal Prediction of Fine-Grained Origin-Destination Matrices with Applications in Ridesharing. CoRR abs/2503.24237 (2025) - [i37]Runpeng Dai, Run Yang, Fan Zhou, Hongtu Zhu:
Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models. CoRR abs/2504.03714 (2025) - [i36]Guohao Shen, Runpeng Dai, Guojun Wu, Shikai Luo, Chengchun Shi, Hongtu Zhu:
Deep Distributional Learning with Non-crossing Quantile Network. CoRR abs/2504.08215 (2025) - 2024
- [j53]Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Ming-Xia Liu:
Source-free unsupervised domain adaptation: A survey. Neural Networks 174: 106230 (2024) - [j52]Qianqian Wang, Wei Wang, Yuqi Fang, Pew-Thian Yap, Hongtu Zhu, Hong-Jun Li, Lishan Qiao, Mingxia Liu:
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI. IEEE Trans. Biomed. Eng. 71(8): 2391-2401 (2024) - [j51]Shixiang Wan, Shikai Luo, Hongtu Zhu:
Causal Probabilistic Spatio-Temporal Fusion Transformers in Two-Sided Ride-Hailing Markets. ACM Trans. Spatial Algorithms Syst. 10(3): 28:1-28:18 (2024) - [c62]Xin Wang, Xiaoyu Liu, Peng Huang, Pu Huang, Shu Hu, Hongtu Zhu:
U-MedSAM: Uncertainty-Aware MedSAM for Medical Image Segmentation. MedSAM@CVPR 2024: 206-217 - [c61]Ying Huang, Zhengwang Wu, Ya Wang, Tengfei Li, Xifeng Wang, Hongtu Zhu, Weili Lin, Li Wang, Jun Feng, John H. Gilmore, Gang Li:
Revealing Fine-grained Genetically Informed Cortical Parcellation Maps of Neonates Based on Multi-view Spectral Clustering. EMBC 2024: 1-4 - [c60]Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao:
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. EMNLP 2024: 1081-1093 - [c59]Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu:
Combining Experimental and Historical Data for Policy Evaluation. ICML 2024 - [c58]Ting Yu Tsai, Li Lin, Shu Hu, Ming-Ching Chang, Hongtu Zhu, Xin Wang:
UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation. MIPR 2024: 267-273 - [c57]Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Y. Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. NeurIPS 2024 - [i35]Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Hongtu Zhu, Tianfan Fu, Huaxiu Yao:
Multimodal Clinical Trial Outcome Prediction with Large Language Models. CoRR abs/2402.06512 (2024) - [i34]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Framework. CoRR abs/2402.06875 (2024) - [i33]Xin Wang, Shu Hu, Heng Fan, Hongtu Zhu, Xin Li:
Neural Radiance Fields in Medical Imaging: Challenges and Next Steps. CoRR abs/2402.17797 (2024) - [i32]Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu:
Combining Experimental and Historical Data for Policy Evaluation. CoRR abs/2406.00317 (2024) - [i31]Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. CoRR abs/2406.06007 (2024) - [i30]Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao:
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. CoRR abs/2407.05131 (2024) - [i29]Runpeng Dai, Jianing Wang, Fan Zhou, Shikai Luo, Zhiwei Qin, Chengchun Shi, Hongtu Zhu:
Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences. CoRR abs/2407.17910 (2024) - [i28]Xin Wang, Xiaoyu Liu, Peng Huang, Pu Huang, Shu Hu, Hongtu Zhu:
U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation. CoRR abs/2408.08881 (2024) - [i27]Ting Yu Tsai, Li Lin, Shu Hu, Connie W. Tsao, Xin Li, Ming-Ching Chang, Hongtu Zhu, Xin Wang:
UU-Mamba: Uncertainty-aware U-Mamba for Cardiovascular Segmentation. CoRR abs/2409.14305 (2024) - [i26]Yongheng Sun, Yueh Z. Lee, Genevieve A. Woodard, Hongtu Zhu, Chunfeng Lian, Mingxia Liu:
R2Gen-Mamba: A Selective State Space Model for Radiology Report Generation. CoRR abs/2410.18135 (2024) - [i25]Zhaoyang Zhang, Ziqi Chen, Qiao Liu, Jinhan Xie, Hongtu Zhu:
Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation. CoRR abs/2411.04899 (2024) - [i24]Zhaoyang Zhang, Hongtu Zhu, Ziqi Chen, Yingjie Zhang, Hai Shu:
Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph. CoRR abs/2411.04907 (2024) - [i23]Kangyu Zhu, Peng Xia, Yun Li, Hongtu Zhu, Sheng Wang, Huaxiu Yao:
MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization. CoRR abs/2412.06141 (2024) - 2023
- [c56]Shuai Li, Ziqi Chen, Hongtu Zhu, Christina Dan Wang, Wang Wen:
Nearest-Neighbor Sampling Based Conditional Independence Testing. AAAI 2023: 8631-8639 - [c55]Yang Sui, Yukun Huang, Hongtu Zhu, Fan Zhou:
Adversarial Learning of Distributional Reinforcement Learning. ICML 2023: 32783-32796 - [c54]Chengming Feng, Jing Hu, Xin Wang, Shu Hu, Bin Zhu, Xi Wu, Hongtu Zhu, Siwei Lyu:
Controlling Neural Style Transfer with Deep Reinforcement Learning. IJCAI 2023: 100-108 - [c53]Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu:
DNet: Distributional Network for Distributional Individualized Treatment Effects. KDD 2023: 5215-5224 - [c52]Zhiwei (Tony) Qin, Rui Song, Jieping Ye, Hongtu Zhu, Michael I. Jordan:
KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. KDD 2023: 5878-5879 - [c51]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu:
Structural MRI Harmonization via Disentangled Latent Energy-Based Style Translation. MLMI@MICCAI (1) 2023: 1-11 - [c50]Ting Li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu:
Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making. NeurIPS 2023 - [c49]Shuai Li, Yingjie Zhang, Hongtu Zhu, Christina Dan Wang, Hai Shu, Ziqi Chen, Zhuoran Sun, Yanfeng Yang:
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing. NeurIPS 2023 - [i22]Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu:
Source-Free Unsupervised Domain Adaptation: A Survey. CoRR abs/2301.00265 (2023) - [i21]Shuai Li, Ziqi Chen, Hongtu Zhu, Christina Dan Wang, Wang Wen:
Nearest-Neighbor Sampling Based Conditional Independence Testing. CoRR abs/2304.04183 (2023) - [i20]Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li, Hongtu Zhu:
Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing. CoRR abs/2305.10187 (2023) - [i19]Qianqian Wang, Wei Wang, Yuqi Fang, Pew-Thian Yap, Hongtu Zhu, Hong-Jun Li, Lishan Qiao, Mingxia Liu:
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI. CoRR abs/2306.14080 (2023) - [i18]Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, Peng Shu, Yaonai Wei, Zihao Wu, Chong Ma, Jiaqi Wang, Sheng Wang, Mengyue Zhou, Zuowei Jiang, Chunlin Li, Jason Holmes, Shaochen Xu, Lu Zhang, Haixing Dai, Kai Zhang, Lin Zhao, Yuanhao Chen, Xu Liu, Peilong Wang, Pingkun Yan, Jun Liu, Bao Ge, Lichao Sun, Dajiang Zhu, Xiang Li, Wei Liu, Xiaoyan Cai, Xintao Hu, Xi Jiang, Shu Zhang, Xin Zhang, Tuo Zhang, Shijie Zhao, Quanzheng Li, Hongtu Zhu, Dinggang Shen, Tianming Liu:
Evaluating Large Language Models for Radiology Natural Language Processing. CoRR abs/2307.13693 (2023) - [i17]Chengming Feng, Jing Hu, Xin Wang, Shu Hu, Bin Zhu, Xi Wu, Hongtu Zhu, Siwei Lyu:
Controlling Neural Style Transfer with Deep Reinforcement Learning. CoRR abs/2310.00405 (2023) - [i16]Xinyu Gong, Jason Holmes, Yiwei Li, Zhengliang Liu, Qi Gan, Zihao Wu, Jianli Zhang, Yusong Zou, Yuxi Teng, Tian Jiang, Hongtu Zhu, Wei Liu, Tianming Liu, Yajun Yan:
Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions. CoRR abs/2311.07582 (2023) - 2022
- [j50]Jiawen Chen, Weifang Liu, Tianyou Luo, Zhentao Yu, Minzhi Jiang, Jia Wen, Gaorav P. Gupta, Paola Giusti, Hongtu Zhu, Yuchen Yang, Yun Li:
A comprehensive comparison on cell-type composition inference for spatial transcriptomics data. Briefings Bioinform. 23(4) (2022) - [j49]Di Xiong, Shihui Ying, Hongtu Zhu:
Intrinsic partial linear models for manifold-valued data. Inf. Process. Manag. 59(4): 102954 (2022) - [j48]Hai Shu, Zhe Qu, Hongtu Zhu:
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data. J. Mach. Learn. Res. 23: 169:1-169:64 (2022) - [j47]Chao Huang, Zhenlin Xu, Zhengyang Shen, Tianyou Luo, Tengfei Li, Daniel Nissman, Amanda Nelson, Yvonne Golightly, Marc Niethammer, Hongtu Zhu:
DADP: Dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the Osteoarthritis Initiative. Medical Image Anal. 77: 102343 (2022) - [j46]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond. SIGKDD Explor. 24(2): 78-80 (2022) - [c48]Hai Shu, Ronghua Shi, Qiran Jia, Hongtu Zhu, Ziqi Chen:
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks. IJCNN 2022: 1-8 - [c47]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond. KDD 2022: 4898-4899 - [i15]Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu:
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. CoRR abs/2202.10574 (2022) - [i14]Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song:
Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process. CoRR abs/2202.10589 (2022) - [i13]Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu:
Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms. CoRR abs/2202.10887 (2022) - [i12]Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song:
Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons. CoRR abs/2202.13163 (2022) - [i11]Shu Wan, Chen Zheng, Zhonggen Sun, Mengfan Xu, Xiaoqing Yang, Hongtu Zhu, Jiecheng Guo:
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace. CoRR abs/2203.10975 (2022) - 2021
- [j45]Ting Li, Xinyuan Song, Yingying Zhang, Hongtu Zhu, Zhongyi Zhu:
Clusterwise functional linear regression models. Comput. Stat. Data Anal. 158: 107192 (2021) - [j44]Meiling Hao, Lianqiang Qu, Dehan Kong, Liuquan Sun, Hongtu Zhu:
Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model. J. Mach. Learn. Res. 22: 147:1-147:39 (2021) - [j43]Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song:
An Online Sequential Test for Qualitative Treatment Effects. J. Mach. Learn. Res. 22: 286:1-286:51 (2021) - [j42]Junghi Kim, Hongtu Zhu, Xiao Wang, Kim-Anh Do:
Scalable network estimation with L0 penalty. Stat. Anal. Data Min. 14(1): 18-30 (2021) - [c46]Chunyi Liu, Hao Feng, Jiang Xu, Zhiwei Tony Qin, Hongtu Zhu:
Optimizing Bike-Share Repositioning: Networked Inventory Management with Spatiotemporal Modeling. IEEE BigData 2021: 1438-1448 - [c45]Fan Zhou, Chenfan Lu, Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Jieping Ye, Hongtu Zhu:
Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching. ICDM 2021: 1541-1546 - [c44]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. ITSC 2021: 2447-2454 - [c43]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. KDD 2021: 3605-3615 - [i10]Yan Jiao, Xiaocheng Tang, Zhiwei (Tony) Qin, Shuaiji Li, Fan Zhang, Hongtu Zhu, Jieping Ye:
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning. CoRR abs/2103.04555 (2021) - [i9]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. CoRR abs/2105.01099 (2021) - [i8]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. CoRR abs/2105.08791 (2021) - [i7]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. CoRR abs/2106.04493 (2021) - 2020
- [j41]Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Fan Zhang, Zhe Xu, Hongtu Zhu, Jieping Ye:
Ride-Hailing Order Dispatching at DiDi via Reinforcement Learning. INFORMS J. Appl. Anal. 50(5): 272-286 (2020) - [j40]Ziqi Chen, Jianhua Hu, Hongtu Zhu:
Surface functional models. J. Multivar. Anal. 180: 104664 (2020) - [j39]Moritz Gerstung, Clemency Jolly, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Kaixian Yu, Maxime Tarabichi, Amit G. Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vázquez-García, Kerstin Haase, Lara Jerman, Subhajit Sengupta, Geoff MacIntyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Marek Cmero, Jonas Demeulemeester, Steven E. Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. L. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, Süleyman Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Yuan, Wenyi Wang, Quaid D. Morris, David J. Adams, Peter J. Campbell, Shaolong Cao, Elizabeth L. Christie, Yupeng Cun, Kevin J. Dawson, Ruben M. Drews, Roland Eils, Matthew Fittall, Dale W. Garsed, Gavin Ha, Henry Lee-Six, Iñigo Martincorena, Layla Oesper, Myron Peto, Benjamin J. Raphael, Daniel T. Rosebrock, Adriana Salcedo, Ruian Shi, Seung Jun Shin, Oliver Spiro, Lincoln D. Stein, Shankar Vembu, David A. Wheeler, Tsun-Po Yang, Paul T. Spellman, David C. Wedge, Peter Van Loo:
The evolutionary history of 2,658 cancers. Nat. 578(7793): 122-128 (2020) - [j38]Liming Zhong, Tengfei Li, Hai Shu, Chao Huang, Jason M. Johnson, Donald F. Schomer, Ho-Ling Liu, Qianjin Feng, Wei Yang, Hongtu Zhu:
(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients. NeuroImage 223: 117368 (2020) - [c42]Jiarui Tang, Tengfei Li, Hai Shu, Hongtu Zhu:
Variational-Autoencoder Regularized 3D MultiResUNet for the BraTS 2020 Brain Tumor Segmentation. BrainLes@MICCAI (2) 2020: 431-440 - [c41]Guojun Wu, Yanhua Li, Shikai Luo, Ge Song, Qichao Wang, Jing He, Jieping Ye, Xiaohu Qie, Hongtu Zhu:
A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction. CIKM 2020: 2805-2812 - [i6]Hai Shu, Zhe Qu, Hongtu Zhu:
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multiple High-dimensional Datasets. CoRR abs/2001.02856 (2020) - [i5]Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye:
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR abs/2002.01711 (2020) - [i4]Ronghua Shi, Hai Shu, Hongtu Zhu, Ziqi Chen:
Adversarial Image Generation and Training for Deep Convolutional Neural Networks. CoRR abs/2006.03243 (2020)
2010 – 2019
- 2019
- [j37]Haiqiang Ma, Ting Li, Hongtu Zhu, Zhongyi Zhu:
Quantile regression for functional partially linear model in ultra-high dimensions. Comput. Stat. Data Anal. 129: 135-147 (2019) - [j36]Brittany R. Howell, Martin A. Styner, Wei Gao, Pew-Thian Yap, Li Wang, Kristine Baluyot, Essa Yacoub, Geng Chen, Taylor Potts, Andrew P. Salzwedel, Gang Li, John H. Gilmore, Joseph Piven, J. Keith Smith, Dinggang Shen, Kâmil Ugurbil, Hongtu Zhu, Weili Lin, Jed T. Elison:
The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development. NeuroImage 185: 891-905 (2019) - [j35]Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu, David B. Dunson:
Tensor network factorizations: Relationships between brain structural connectomes and traits. NeuroImage 197: 330-343 (2019) - [j34]Brittany R. Howell, Mihye Ahn, Yundi Shi, Jodi R. Godfrey, Xiaoping Hu, Hongtu Zhu, Martin Styner, Mar Sanchez:
Disentangling the effects of early caregiving experience and heritable factors on brain white matter development in rhesus monkeys. NeuroImage 197: 625-642 (2019) - [c40]Zhenhua Lin, Hongtu Zhu:
MFPCA: Multiscale Functional Principal Component Analysis. AAAI 2019: 4320-4327 - [c39]Hai Shu, Hongtu Zhu:
Sensitivity Analysis of Deep Neural Networks. AAAI 2019: 4943-4950 - [c38]Jingwen Zhang, Joseph G. Ibrahim, Tengfei Li, Hongtu Zhu:
A Powerful Global Test Statistic for Functional Statistical Inference. AAAI 2019: 5765-5772 - [c37]Tao Huang, Yintai Ma, Zhiwei (Tony) Qin, Jianfeng Zheng, Henry X. Liu, Hongtu Zhu, Jieping Ye:
Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network. IEEE BigData 2019: 1450-1459 - [c36]Weinan Zhang, Haiming Jin, Lingyu Zhang, Hongtu Zhu, Zhenhui Jessie Li, Jieping Ye:
CIKM 2019 Workshop on Artificial Intelligence in Transportation (AI in transportation). CIKM 2019: 2995-2996 - [c35]Haipeng Chen, Yan Jiao, Zhiwei (Tony) Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye:
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms. ICDM 2019: 61-70 - [c34]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. KDD 2019: 1780-1790 - [c33]Tengfei Li, Xifeng Wang, Tianyou Luo, Yue Yang, Bingxin Zhao, Liuqing Yang, Ziliang Zhu, Hongtu Zhu:
Adolescent Fluid Intelligence Prediction from Regional Brain Volumes and Cortical Curvatures Using BlockPC-XGBoost. ABCD-NP@MICCAI 2019: 167-175 - [c32]Fan Zhou, Tengfei Li, Haibo Zhou, Hongtu Zhu, Jieping Ye:
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response. NeurIPS 2019: 7013-7023 - [i3]Hai Shu, Hongtu Zhu:
Sensitivity Analysis of Deep Neural Networks. CoRR abs/1901.07152 (2019) - [i2]Zhenyu Shou, Xuan Di, Jieping Ye, Hongtu Zhu, Robert C. Hampshire:
Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach. CoRR abs/1905.09906 (2019) - 2018
- [j33]Ching-Wei Wang, Yu-Ching Lee, Evelyne Calista, Fan Zhou, Hongtu Zhu, Ryohei Suzuki, Daisuke Komura, Shumpei Ishikawa, Shih-Ping Cheng:
A benchmark for comparing precision medicine methods in thyroid cancer diagnosis using tissue microarrays. Bioinform. 34(10): 1767-1773 (2018) - [j32]Priscille de Dumast, Clément Mirabel, Lucia H. S. Cevidanes, Antonio C. Ruellas, Marilia Yatabe, Marcos Ioshida, Nina Tubau Ribera, Loic Michoud, Liliane R. Gomes, Chao Huang, Hongtu Zhu, Luciana Muniz, Brandon Shoukri, Beatriz Paniagua, Martin Styner, Steve Pieper, François Budin, Jean-Baptiste Vimort, Juan-Carlos Prieto:
A web-based system for neural network based classification in temporomandibular joint osteoarthritis. Comput. Medical Imaging Graph. 67: 45-54 (2018) - [j31]Zhengwu Zhang, Maxime Descoteaux, Jingwen Zhang, Gabriel Girard, Maxime Chamberland, David B. Dunson, Anuj Srivastava, Hongtu Zhu:
Mapping population-based structural connectomes. NeuroImage 172: 130-145 (2018) - [j30]Leo Yu-Feng Liu, Yufeng Liu, Hongtu Zhu, Alzheimer's Disease Neuroimaging Initiative:
SMAC: Spatial multi-category angle-based classifier for high-dimensional neuroimaging data. NeuroImage 175: 230-245 (2018) - [c31]Zhaodong Wang, Zhiwei (Tony) Qin, Xiaocheng Tang, Jieping Ye, Hongtu Zhu:
Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching. ICDM 2018: 617-626 - [c30]Tengfei Li, Fan Zhou, Ziliang Zhu, Hai Shu, Hongtu Zhu:
A label-fusion-aided convolutional neural network for isointense infant brain tissue segmentation. ISBI 2018: 692-695 - [c29]Rongjie Liu, Chao Huang, Tengfei Li, Liuqing Yang, Hongtu Zhu:
Statistical disease mapping for heterogeneous neuroimaging studies. ISBI 2018: 1415-1418 - [c28]Jared Vicory, Laura Pascal, Pablo Hernandez, James Fishbaugh, Juan-Carlos Prieto, Mahmoud Mostapha, Chao Huang, Hina Shah, Jun-Pyo Hong, Zhiyuan Liu, Loic Michoud, Jean-Christophe Fillion-Robin, Guido Gerig, Hongtu Zhu, Stephen M. Pizer, Martin Styner, Beatriz Paniagua:
SlicerSALT: Shape AnaLysis Toolbox. ShapeMI@MICCAI 2018: 65-72 - [c27]Lutao Dai, Tengfei Li, Hai Shu, Liming Zhong, Haipeng Shen, Hongtu Zhu:
Automatic Brain Tumor Segmentation with Domain Adaptation. BrainLes@MICCAI (2) 2018: 380-392 - 2017
- [j29]Wensheng Zhu, Ying Yuan, Jingwen Zhang, Fan Zhou, Rebecca C. Knickmeyer, Hongtu Zhu:
Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study. NeuroImage 146: 983-1002 (2017) - [j28]Zhaohua Lu, Zakaria Khondker, Joseph G. Ibrahim, Yue Wang, Hongtu Zhu:
Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies. NeuroImage 149: 305-322 (2017) - [j27]Chao Huang, Paul M. Thompson, Yalin Wang, Yang Yu, Jingwen Zhang, Dehan Kong, Rivka R. Colen, Rebecca C. Knickmeyer, Hongtu Zhu, Alzheimer's Disease Neuroimaging Initiative:
FGWAS: Functional genome wide association analysis. NeuroImage 159: 107-121 (2017) - [c26]Wenliang Pan, Xueqin Wang, Canhong Wen, Martin Styner, Hongtu Zhu:
Conditional Local Distance Correlation for Manifold-Valued Data. IPMI 2017: 41-52 - [c25]Jingwen Zhang, Chao Huang, Joseph G. Ibrahim, Shaili Jha, Rebecca C. Knickmeyer, John H. Gilmore, Martin Styner, Hongtu Zhu:
HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics. IPMI 2017: 478-489 - [c24]Fan Zhou, Tengfei Li, Heng Li, Hongtu Zhu:
TPCNN: Two-Phase Patch-Based Convolutional Neural Network for Automatic Brain Tumor Segmentation and Survival Prediction. BrainLes@MICCAI 2017: 274-286 - [e1]Marc Niethammer, Martin Styner, Stephen R. Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen:
Information Processing in Medical Imaging - 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings. Lecture Notes in Computer Science 10265, Springer 2017, ISBN 978-3-319-59049-3 [contents] - 2016
- [j26]Jung Won Hyun, Yimei Li, Chao Huang, Martin Styner, Weili Lin, Hongtu Zhu:
STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data. NeuroImage 134: 550-562 (2016) - [c23]Shan Yang, Vladimir Jojic, Jun Lian, Ronald C. Chen, Hongtu Zhu, Ming C. Lin:
Classification of Prostate Cancer Grades and T-Stages Based on Tissue Elasticity Using Medical Image Analysis. MICCAI (1) 2016: 627-635 - [i1]Yao Chen, Xiao Wang, Linglong Kong, Hongtu Zhu:
Local Region Sparse Learning for Image-on-Scalar Regression. CoRR abs/1605.08501 (2016) - 2015
- [j25]Seung Jae Lee, Rachel J. Steiner, Shikai Luo, Michael C. Neale, Martin Styner, Hongtu Zhu, John H. Gilmore:
Quantitative tract-based white matter heritability in twin neonates. NeuroImage 111: 123-135 (2015) - [j24]Meiyan Huang, Thomas E. Nichols, Chao Huang, Yang Yu, Zhaohua Lu, Rebecca C. Knickmeyer, Qianjin Feng, Hongtu Zhu:
FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data. NeuroImage 118: 613-627 (2015) - [j23]Qibing Gao, Mihye Ahn, Hongtu Zhu:
Cook's Distance Measures for Varying Coefficient Models With Functional Responses. Technometrics 57(2): 268-280 (2015) - [j22]Chao Huang, Liang Shan, Cecil Charles, Wolfgang Wirth, Marc Niethammer, Hongtu Zhu:
Diseased Region Detection of Longitudinal Knee Magnetic Resonance Imaging Data. IEEE Trans. Medical Imaging 34(9): 1914-1927 (2015) - [c22]Dan Shen, Hongtu Zhu:
Spatially Weighted Principal Component Regression for High-Dimensional Prediction. IPMI 2015: 758-769 - [c21]Xinchao Luo, Lixing Zhu, Linglong Kong, Hongtu Zhu:
Functional Nonlinear Mixed Effects Models for Longitudinal Image Data. IPMI 2015: 794-805 - 2014
- [j21]Ying Yuan, John H. Gilmore, Xiujuan Geng, Martin Andreas Styner, Kehui Chen, Jane-Ling Wang, Hongtu Zhu:
FMEM: Functional mixed effects modeling for the analysis of longitudinal white matter Tract data. NeuroImage 84: 753-764 (2014) - [j20]Jung Won Hyun, Yimei Li, John H. Gilmore, Zhaohua Lu, Martin Andreas Styner, Hongtu Zhu:
SGPP: spatial Gaussian predictive process models for neuroimaging data. NeuroImage 89: 70-80 (2014) - [c20]Yasheng Chen, Hongyu An, Dinggang Shen, Hongtu Zhu, Weili Lin:
Tailor the longitudinal anaysis for nih longitudinal normal brain developmental study. ISBI 2014: 1206-1209 - 2013
- [j19]Audrey R. Verde, François Budin, Jean-Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Mihye Ahn, Hans J. Johnson, Joy T. Matsui, Heather Cody Hazlett, Anuja Sharma, Casey Goodlett, Yundi Shi, Sylvain Gouttard, Clement Vachet, Joseph Piven, Hongtu Zhu, Guido Gerig, Martin Andreas Styner:
UNC-Utah NA-MIC framework for DTI fiber tract analysis. Frontiers Neuroinformatics 7: 51 (2013) - [j18]Yimei Li, John H. Gilmore, Dinggang Shen, Martin Styner, Weili Lin, Hongtu Zhu:
Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data. NeuroImage 72: 91-105 (2013) - [c19]Ying Yuan, John H. Gilmore, Xiujuan Geng, Martin Andreas Styner, Kehui Chen, Jane-Ling Wang, Hongtu Zhu:
A Longitudinal Functional Analysis Framework for Analysis of White Matter Tract Statistics. IPMI 2013: 220-231 - [c18]Chao Huang, Liang Shan, Cecil Charles, Marc Niethammer, Hongtu Zhu:
Diseased Region Detection of Longitudinal Knee MRI Data. IPMI 2013: 632-643 - [c17]Audrey R. Verde, Jean-Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Vicki W. Chanon, Charlotte A. Boettiger, Hans J. Johnson, Joy T. Matsui, Anuja Sharma, Casey Goodlett, Yundi Shi, Hongtu Zhu, Guido Gerig, Sylvain Gouttard, Clement Vachet, Martin Styner:
UNC-Utah NA-MIC DTI framework: atlas based fiber tract analysis with application to a study of nicotine smoking addiction. Image Processing 2013: 86692D - [c16]Yaping Wang, Gang Li, Mihye Ahn, Jingxin Nie, Hongtu Zhu, Lei Guo:
Mapping longitudinal cerebral cortex development using diffusion tensor imaging. Image Processing 2013: 86692E - 2012
- [j17]Zhaowei Hua, David B. Dunson, John H. Gilmore, Martin Andreas Styner, Hongtu Zhu:
Semiparametric Bayesian local functional models for diffusion tensor tract statistics. NeuroImage 63(1): 460-474 (2012) - [j16]Jiaping Wang, Haipeng Shen, Hongtu Zhu:
Comment. Technometrics 54(2): 129-133 (2012) - [j15]Yimei Li, John H. Gilmore, Jiaping Wang, Martin Styner, Weili Lin, Hongtu Zhu:
TwinMARM: Two-Stage Multiscale Adaptive Regression Methods for Twin Neuroimaging Data. IEEE Trans. Medical Imaging 31(5): 1100-1112 (2012) - 2011
- [j14]Beatriz Paniagua, Lucia H. S. Cevidanes, Hongtu Zhu, Martin Styner:
Outcome quantification using SPHARM-PDM toolbox in orthognathic surgery. Int. J. Comput. Assist. Radiol. Surg. 6(5): 617-626 (2011) - [j13]Beatriz Paniagua, Lucia H. S. Cevidanes, David Walker, Hongtu Zhu, Ruixin Guo, Martin Styner:
Clinical application of SPHARM-PDM to quantify temporomandibular joint osteoarthritis. Comput. Medical Imaging Graph. 35(5): 345-352 (2011) - [j12]Martha Skup, Hongtu Zhu, Yaping Wang, Kelly S. Giovanello, Ja-an Lin, Dinggang Shen, Feng Shi, Wei Gao, Weili Lin, Yong Fan, Heping Zhang:
Sex differences in grey matter atrophy patterns among AD and aMCI patients: Results from ADNI. NeuroImage 56(3): 890-906 (2011) - [j11]Hongtu Zhu, Linglong Kong, Runze Li, Martin Styner, Guido Gerig, Weili Lin, John H. Gilmore:
FADTTS: Functional analysis of diffusion tensor tract statistics. NeuroImage 56(3): 1412-1425 (2011) - [j10]Yasheng Chen, Hongyu An, Hongtu Zhu, Valerie Jewells, Diane Armao, Dinggang Shen, John H. Gilmore, Weili Lin:
Longitudinal regression analysis of spatial-temporal growth patterns of geometrical diffusion measures in early postnatal brain development with diffusion tensor imaging. NeuroImage 58(4): 993-1005 (2011) - [c15]Yimei Li, John H. Gilmore, Jiaping Wang, Martin Styner, Weili Lin, Hongtu Zhu:
Two-Stage Multiscale Adaptive Regression Methods for Twin Neuroimaging Data. MBIA 2011: 102-109 - [c14]Jiaping Wang, Hongtu Zhu, Jianqing Fan, Kelly S. Giovanello, Weili Lin:
Adaptively and Spatially Estimating the Hemodynamic Response Functions in fMRI. MICCAI (2) 2011: 269-276 - 2010
- [j9]Hongtu Zhu, Martin Styner, Niansheng Tang, Zhexing Liu, Weili Lin, John H. Gilmore:
FRATS: Functional Regression Analysis of DTI Tract Statistics. IEEE Trans. Medical Imaging 29(4): 1039-1049 (2010) - [j8]Pew-Thian Yap, Guorong Wu, Hongtu Zhu, Weili Lin, Dinggang Shen:
F-TIMER: Fast Tensor Image Morphing for Elastic Registration. IEEE Trans. Medical Imaging 29(5): 1192-1203 (2010) - [c13]Yasheng Chen, Songbai Ji, Xunlei Wu, Hongyu An, Hongtu Zhu, Dinggang Shen, Weili Lin:
Simulation of Brain Mass Effect with an Arbitrary Lagrangian and Eulerian FEM. MICCAI (2) 2010: 274-281 - [c12]Wei Gao, Hongtu Zhu, Kelly S. Giovanello, Weili Lin:
Multivariate Network-Level Approach to Detect Interactions between Large-Scale Functional Systems. MICCAI (2) 2010: 298-305 - [c11]Hongtu Zhu, Martin Styner, Yimei Li, Linglong Kong, Yundi Shi, Weili Lin, Christopher L. Coe, John H. Gilmore:
Multivariate Varying Coefficient Models for DTI Tract Statistics. MICCAI (1) 2010: 690-697
2000 – 2009
- 2009
- [j7]Wei Gao, Hongtu Zhu, Weili Lin:
A unified optimization approach for diffusion tensor imaging technique. NeuroImage 44(3): 729-741 (2009) - [j6]Pew-Thian Yap, Guorong Wu, Hongtu Zhu, Weili Lin, Dinggang Shen:
TIMER: Tensor Image Morphing for Elastic Registration. NeuroImage 47(2): 549-563 (2009) - [j5]Yasheng Chen, Hongyu An, Hongtu Zhu, Taylor Stone, J. Keith Smith, Colin Hall, Elizabeth Bullitt, Dinggang Shen, Weili Lin:
White matter abnormalities revealed by diffusion tensor imaging in non-demented and demented HIV+ patients. NeuroImage 47(4): 1154-1162 (2009) - [c10]Pew-Thian Yap, Guorong Wu, Hongtu Zhu, Weili Lin, Dinggang Shen:
TIMER: Tensor Image Morphing for Elastic Registration. CVPR Workshops 2009: 1-8 - [c9]Songyuan Tang, Yong Fan, Hongtu Zhu, Pew-Thian Yap, Wei Gao, Weili Lin, Dinggang Shen:
Regularization of diffusion tensor field using coupled robust anisotropic diffusion filters. CVPR Workshops 2009: 52-57 - [c8]Hongtu Zhu, Yimei Li, Joseph G. Ibrahim, Weili Lin, Dinggang Shen:
MARM: Multiscale Adaptive Regression Models for Neuroimaging Data. IPMI 2009: 314-325 - [c7]Zhexing Liu, Hongtu Zhu, Bonita Marks, Laurence M. Katz, Casey Goodlett, Guido Gerig, Martin Andreas Styner:
Voxel-Wise Group Analysis of DTI. ISBI 2009: 807-810 - [c6]Xiaoyan Shi, Martin Styner, Jeffrey A. Lieberman, Joseph G. Ibrahim, Weili Lin, Hongtu Zhu:
Intrinsic Regression Models for Manifold-Valued Data. MICCAI (1) 2009: 192-199 - [c5]Yasheng Chen, Hongtu Zhu, Dinggang Shen, Hongyu An, John H. Gilmore, Weili Lin:
Mapping Growth Patterns and Genetic Influences on Early Brain Development in Twins. MICCAI (1) 2009: 232-239 - [c4]Pew-Thian Yap, Guorong Wu, Hongtu Zhu, Weili Lin, Dinggang Shen:
Fast Tensor Image Morphing for Elastic Registration. MICCAI (1) 2009: 721-729 - [c3]Yimei Li, Hongtu Zhu, Yasheng Chen, Hongyu An, John H. Gilmore, Weili Lin, Dinggang Shen:
LSTGEE: longitudinal analysis of neuroimaging data. Image Processing 2009: 72590F - [c2]Yimei Li, Hongtu Zhu, Yasheng Chen, Joseph G. Ibrahim, Hongyu An, Weili Lin, Colin Hall, Dinggang Shen:
RADTI: regression analyses of diffusion tensor images. Image Processing 2009: 72591C - [c1]Yasheng Chen, Dinggang Shen, Hongtu Zhu, Hongyu An, John H. Gilmore, Weili Lin:
Hierarchical unbiased group-wise registration for atlas construction and population comparison. Image Processing 2009: 72592V - 2008
- [j4]Ying Yuan, Hongtu Zhu, Joseph G. Ibrahim, Weili Lin, Bradley S. Peterson:
A Note on the Validity of Statistical Bootstrapping for Estimating the Uncertainty of Tensor Parameters in Diffusion Tensor Images. IEEE Trans. Medical Imaging 27(10): 1506-1514 (2008) - 2007
- [j3]Hongtu Zhu, Minggao Gu, Bradley S. Peterson:
Maximum likelihood from spatial random effects models via the stochastic approximation expectation maximization algorithm. Stat. Comput. 17(2): 163-177 (2007) - [j2]Ravi Bansal, Lawrence H. Staib, Dongrong Xu, Hongtu Zhu, Bradley S. Peterson:
Statistical Analyses of Brain Surfaces Using Gaussian Random Fields on 2-D Manifolds. IEEE Trans. Medical Imaging 26(1): 46-57 (2007) - [j1]Hongtu Zhu, Joseph G. Ibrahim, Niansheng Tang, D. B. Rowe, Xuejun Hao, Ravi Bansal, Bradley S. Peterson:
A Statistical Analysis of Brain Morphology Using Wild Bootstrapping. IEEE Trans. Medical Imaging 26(7): 954-966 (2007)
Coauthor Index
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