Gao, Junbin

38 publications

NeurIPS 2025 ACT as Human: Multimodal Large Language Model Data Annotation with Critical Thinking Lequan Lin, Dai Shi, Andi Han, Feng Chen, Qiuzheng Chen, Jiawen Li, Zhaoyang Li, Jiyuan Zhang, Zhenbang Sun, Junbin Gao

ICLR 2025 Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning Lequan Lin, Dai Shi, Andi Han, Zhiyong Wang, Junbin Gao

ICLRW 2025 Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond Dai Shi, Kuan Yan, Lequan Lin, Yue Zeng, Ting Zhang, Jialing Zhang, Matsypura Dmytro, Mark C. Gillies, Ling Zhu, Junbin Gao

AAAI 2025 HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation Tengfei Liu, Jiapu Wang, Yongli Hu, Mingjie Li, Junfei Yi, Xiaojun Chang, Junbin Gao, Baocai Yin

NeurIPS 2025 Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering TianxiangZhao, Youqing Wang, Jinlu Wang, Jiapu Wang, Mingliang Cui, Junbin Gao, Jipeng Guo

ICCV 2025 Language-Driven Multi-Label Zero-Shot Learning with Semantic Granularity Shouwen Wang, Qian Wan, Junbin Gao, Zhigang Zeng

ICLRW 2025 SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting Lequan Lin, Dai Shi, Andi Han, Junbin Gao

ICLR 2025 When Graph Neural Networks Meet Dynamic Mode Decomposition Dai Shi, Lequan Lin, Andi Han, Zhiyong Wang, Yi Guo, Junbin Gao

MLJ 2024 Differentially Private Riemannian Optimization Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

ICML 2024 Diffusion Models Demand Contrastive Guidance for Adversarial Purification to Advance Mingyuan Bai, Wei Huang, Tenghui Li, Andong Wang, Junbin Gao, Cesar F Caiafa, Qibin Zhao

TMLR 2024 From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han, Dai Shi, Lequan Lin, Junbin Gao

AAAI 2024 Graph Neural Networks with Soft Association Between Topology and Attribute Yachao Yang, Yanfeng Sun, Shaofan Wang, Jipeng Guo, Junbin Gao, Fujiao Ju, Baocai Yin

TMLR 2024 Revisiting Generalized P-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion Dai Shi, Zhiqi Shao, Yi Guo, Qibin Zhao, Junbin Gao

MLJ 2024 Riemannian Block SPD Coupling Manifold and Its Application to Optimal Transport Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

TMLR 2024 SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP Jie Chen, Mingyuan Bai, Shouzhen Chen, Junbin Gao, Junping Zhang, Jian Pu

TMLR 2023 Nonconvex-Nonconcave Min-Max Optimization on Riemannian Manifolds Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

AISTATS 2023 Riemannian Accelerated Gradient Methods via Extrapolation Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao

MLJ 2021 Coupling Matrix Manifolds Assisted Optimization for Optimal Transport Problems Dai Shi, Junbin Gao, Xia Hong, S. T. Boris Choy, Zhiyong Wang

ICLRW 2021 Grassmann Graph Embedding Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao

AAAI 2021 Hierarchical Graph Convolution Network for Traffic Forecasting Kan Guo, Yongli Hu, Yanfeng Sun, Sean Qian, Junbin Gao, Baocai Yin

ICML 2021 How Framelets Enhance Graph Neural Networks Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montufar

NeurIPS 2021 On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry Andi Han, Bamdev Mishra, Pratik Kumar Jawanpuria, Junbin Gao

IJCAI 2021 Riemannian Stochastic Recursive Momentum Method for Non-Convex Optimization Andi Han, Junbin Gao

IJCAI 2020 Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding Chengkun Zhang, Junbin Gao

AAAI 2020 Shared Generative Latent Representation Learning for Multi-View Clustering Ming Yin, Weitian Huang, Junbin Gao

IJCAI 2018 Cascaded Low Rank and Sparse Representation on Grassmann Manifolds Boyue Wang, Yongli Hu, Junbin Gao, Yanfeng Sun, Baocai Yin

AAAI 2018 Locality Preserving Projection Based on F-Norm Xiangjie Hu, Yanfeng Sun, Junbin Gao, Yongli Hu, Baocai Yin

CVPR 2017 Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering Qiong Wang, Junbin Gao, Hong Li

IJCAI 2017 Locality Preserving Projections for Grassmann Manifold Boyue Wang, Yongli Hu, Junbin Gao, Yanfeng Sun, Haoran Chen, Muhammad Ali, Baocai Yin

CVPR 2017 Low-Rank-Sparse Subspace Representation for Robust Regression Yongqiang Zhang, Daming Shi, Junbin Gao, Dansong Cheng

CVPR 2016 Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds Ming Yin, Yi Guo, Junbin Gao, Zhaoshui He, Shengli Xie

CVPR 2016 Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis Fujiao Ju, Yanfeng Sun, Junbin Gao, Simeng Liu, Yongli Hu, Baocai Yin

AAAI 2016 Product Grassmann Manifold Representation and Its LRR Models Boyue Wang, Yongli Hu, Junbin Gao, Yanfeng Sun, Baocai Yin

CVPR 2016 Proximal Riemannian Pursuit for Large-Scale Trace-Norm Minimization Mingkui Tan, Shijie Xiao, Junbin Gao, Dong Xu, Anton van den Hengel, Qinfeng Shi

CVPR 2015 Learning Graph Structure for Multi-Label Image Classification via Clique Generation Mingkui Tan, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Junbin Gao, Fuyuan Hu, Zhen Zhang

CVPR 2014 Subspace Clustering for Sequential Data Stephen Tierney, Junbin Gao, Yi Guo

MLJ 2002 A Probabilistic Framework for SVM Regression and Error Bar Estimation Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin Brown

NeCo 2001 On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces Junbin Gao, Chris J. Harris, Steve R. Gunn