Hongxiang Lin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
16
Venues
6
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
16 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CIKM | ConGM: Contrastive Graph Matching for Graph Self-Supervised Learning. | Hongxiang Lin, Lei Wang, Huiying Hu, Xiaoqing Lyu |
| 2025 | KDD | SMA-GNN: A Symbol-Aware Graph Neural Network for Signed Link Prediction in Recommender Systems. | Yumeng Zhao, Hongxiang Lin, Shuo Wen, Junjie Shen, Bei Hua |
| 2025 | SIGIR | Improving Link Sign Prediction in Signed Bipartite Graphs via Balanced Line Graphs. | Hongxiang Lin, Yixiao Zhou, Huiying Hu, Xiaoqing Lyu |
| 2025 | SIGIR | Multi-Interest Matching for Personalized News Recommendation with Large Language Models. | Hongxiang Lin, Yixiao Zhou, Huiying Hu, Xiaoqing Lyu |
| 2024 | ICASSP | Stable Optimization for Large Vision Model Based Deep Image Prior in Cone-Beam CT Reconstruction. | Minghui Wu, Yangdi Xu, Yingying Xu, Guangwei Wu, Qingqing Chen, Hongxiang Lin |
| 2023 | CIKM | Boosting Meta-Learning Cold-Start Recommendation with Graph Neural Network. | Han Liu, Hongxiang Lin, Xiaotong Zhang, Fenglong Ma, Hongyang Chen, Lei Wang, Hong Yu, Xianchao Zhang |
| 2023 | MICCAI | 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 |
| 2023 | SIGIR | Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning. | Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu |
| 2022 | MICCAI | Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. | Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander |
| 2021 | ICANN | AMVAE: Asymmetric Multimodal Variational Autoencoder for Multi-view Representation. | Wen Youpeng, Hongxiang Lin, Guo Yiju, Zhao Liang |
| 2021 | MICCAI | Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts. | Hongxiang Lin, Yukun Zhou, Paddy J. Slator, Daniel C. Alexander |
| 2021 | MICCAI | 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 |
| 2019 | MICCAI | 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, Daniel C. Alexander |
| 2019 | MICCAI | ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression. | goston 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, Daniil I. Nikitichev, Janaina Mouro Miranda, Neil P. Oxtoby |
| 2019 | MICCAI | ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology. | Neil P. Oxtoby, Fabio S. Ferreira, goston Mihalik, Tong Wu, Mikael Brudfors, Hongxiang Lin, Anita Rau, Stefano B. Blumberg, Maria Robu, Cemre Zor, Maira Tariq, Mar Estarellas Garcia, Baris Kanber, Daniil I. Nikitichev, Janaina Mouro Miranda |
| 2018 | MICCAI | Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors. | Hongxiang Lin, Takashi Azuma, Mehmet Burcin Unlu, Shu Takagi |