Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors. - Hongxiang Lin; Takashi Azuma; Mehmet Burcin Unlu; Shu Takagi (MICCAI (1), 2018)

Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator. - Hongxiang Lin; Matteo Figini; Ryutaro Tanno; Stefano B. Blumberg; Enrico Kaden; Godwin Ogbole; Biobele J. Brown; Felice D'Arco; David W. Carmichael; Ikeoluwa Lagunju; Helen J. Cross; Delmiro Fernandez-Reyes; et al. (MLMIR@MICCAI, 2019)

ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression. - Ágoston Mihalik; Mikael Brudfors; Maria Robu; Fabio S. Ferreira; Hongxiang Lin; Anita Rau; Tong Wu; Stefano B. Blumberg; Baris Kanber; Maira Tariq; Mar Estarellas Garcia; Cemre Zor; et al. (ABCD-NP@MICCAI, 2019)

ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology. - Neil P. Oxtoby; Fabio S. Ferreira; Ágoston Mihalik; Tong Wu; Mikael Brudfors; Hongxiang Lin; Anita Rau; Stefano B. Blumberg; Maria Robu; Cemre Zor; Maira Tariq; Mar Estarellas Garcia; et al. (ABCD-NP@MICCAI, 2019)

Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients. - Matteo Figini; Hongxiang Lin; Godwin Ogbole; Felice D'Arco; Stefano B. Blumberg; David W. Carmichael; Ryutaro Tanno; Enrico Kaden; Biobele J. Brown; Ikeoluwa Lagunju; Helen J. Cross; Delmiro Fernandez-Reyes; et al. (CoRR, 2020)

AMVAE: Asymmetric Multimodal Variational Autoencoder for Multi-view Representation. - Wen Youpeng; Hongxiang Lin; Guo Yiju; Zhao Liang (ICANN (1), 2021)

Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts. - Hongxiang Lin; Yukun Zhou; Paddy J. Slator; Daniel C. Alexander (MICCAI (6), 2021)

Learning to Address Intra-segment Misclassification in Retinal Imaging. - Yukun Zhou; Moucheng Xu; Yipeng Hu; Hongxiang Lin; Joseph Jacob; Pearse A. Keane; Daniel C. Alexander (MICCAI (1), 2021)

Continual Contrastive Self-supervised Learning for Image Classification. - Zhiwei Lin; Yongtao Wang; Hongxiang Lin (CoRR, 2021)

Continual Contrastive Learning for Image Classification. - Zhiwei Lin; Yongtao Wang; Hongxiang Lin (ICME, 2022)

Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. - Stefano B. Blumberg; Hongxiang Lin; Francesco Grussu; Yukun Zhou; Matteo Figini; Daniel C. Alexander (MICCAI (6), 2022)

Adaptively Re-weighting Multi-Loss Untrained Transformer for Sparse-View Cone-Beam CT Reconstruction. - Minghui Wu 009; Yangdi Xu; Yingying Xu; Guangwei Wu; Qingqing Chen 001; Hongxiang Lin (CoRR, 2022)

An Experiment Design Paradigm using Joint Feature Selection and Task Optimization. - Stefano B. Blumberg; Hongxiang Lin; Yukun Zhou; Paddy Slator; Daniel C. Alexander (CoRR, 2022)

Enabling Large Language Models to Think Twice When Its Answer Is Unreliable: A Case Study In Cancer Screening. - Minchong Wu; Hongxiang Lin; Xiaoqing Lyu; Chenrui Zhang; Sun Yu (BIBM, 2023)

Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network. - Han Liu 008; Hongxiang Lin; Xiaotong Zhang 003; Fenglong Ma; Hongyang Chen; Lei Wang 005; Hong Yu 005; Xianchao Zhang 001 (CIKM, 2023)

Pulse Stretching Correction for Improving Ultrasound Image Resolution. - Changshan Han; He Huang; Zhengfeng Lan; Zeyu Zhuang; Jingsong Li 001; Hongxiang Lin (EMBC, 2023)

Auto-tuning numerical method for acoustic wave simulation using analytical solution. - He Huang; Zheng Li; Changshan Han; Guangwei Wu; Zeyu Zhuang; Jingsong Li 001; Hongxiang Lin (EMBC, 2023)

A joint method of coherence factor and nonlinear beamforming for synthetic aperture imaging with a ring array. - Zhengfeng Lan; Chao Rong; Changshan Han; Xiaolei Qu; Jingsong Li 001; Hongxiang Lin (EMBC, 2023)

Deep Fusion Network Based Sparse View CT Reconstructions for Clinical Diagnostic Scanners. - Yangdi Xu; Jingsong Li 001; Hongxiang Lin (EMBC, 2023)

PLD-AL: Pseudo-label Divergence-Based Active Learning in Carotid Intima-Media Segmentation for Ultrasound Images. - Yucheng Tang; Yipeng Hu; Jing Li; Hu Lin; Xiang Xu; Ke Huang; Hongxiang Lin (MICCAI (2), 2023)

Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network. - Yixiao Zhou; Ruiqi Jia; Hongxiang Lin; Hefeng Quan; Yumeng Zhao; Xiaoqing Lyu (NeurIPS, 2023)

Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning. - Hongxiang Lin; Ruiqi Jia; Xiaoqing Lyu (SIGIR, 2023)

CT-Based Automatic Spine Segmentation Using Patch-Based Deep Learning. - Syed Furqan Qadri; Hongxiang Lin; Linlin Shen; Mubashir Ahmad; Salman Qadri; Salabat Khan; Maqbool Khan; Syeda Shamaila Zareen; Muhammad Azeem Akbar; Md Belal Bin Heyat; Saqib Qamar (Int. J. Intell. Syst., 2023)

Low-field magnetic resonance image enhancement via stochastic image quality transfer. - Hongxiang Lin; Matteo Figini; Felice D'Arco; Godwin Ogbole; Ryutaro Tanno; Stefano B. Blumberg; Lisa Ronan; Biobele J. Brown; David W. Carmichael; Ikeoluwa Lagunju; Judith Helen Cross; Delmiro Fernandez-Reyes; et al. (Medical Image Anal., 2023)

Graph Matching Based Graph Self-Supervised Learning for Molecular Property Prediction. - Hongxiang Lin; Yixiao Zhou; Huiying Hu; Zhicheng He 011; Runzhi Wu; Xiaoqing Lyu (BIBM, 2024)

Stable Optimization for Large Vision Model Based Deep Image Prior in Cone-Beam CT Reconstruction. - Minghui Wu 009; Yangdi Xu; Yingying Xu; Guangwei Wu; Qingqing Chen 001; Hongxiang Lin (ICASSP, 2024)

FPGA Oriented Lightweight Deep Learning Inference for Liver Cancer Segmentation. - Yingying Xu; Yinjie Wang; Qingqing Chen 001; Hongjie Hu; Huimin Huang 002; Lanfen Lin; Yen-Wei Chen 001; Jingsong Li 001; Hongxiang Lin (ISBI, 2024)

Improving Link Sign Prediction in Signed Bipartite Graphs via Balanced Line Graphs. - Hongxiang Lin; Yixiao Zhou; Huiying Hu; Xiaoqing Lyu (SIGIR, 2025)

Multi-Interest Matching for Personalized News Recommendation with Large Language Models. - Hongxiang Lin; Yixiao Zhou; Huiying Hu; Xiaoqing Lyu (SIGIR, 2025)

When Relevance Meets Novelty: Dual-Stable Periodic Optimization for Exploratory Recommendation. - Hongxiang Lin; Hao Guo; Zeshun Li; Erpeng Xue; Yongqian He; Xiangyu Hou; Zhaoyu Hu; Lei Wang; Sheng Chen (CoRR, 2025)

Dynamic Forgetting and Spatio-Temporal Periodic Interest Modeling for Local-Life Service Recommendation. - Zhaoyu Hu; Hao Guo; Yuan Tian; Erpeng Xue; Jianyang Wang; Xianyang Qi; Hongxiang Lin; Lei Wang; Sheng Chen (CoRR, 2025)