Ribs segmentation based on image fusion and wavelet de-noising. - Wen-cheng Cui; Tianshu Yu 001; Lijie Ren; Hong Shao (BMEI, 2012)

Face recognition based on subset selection via metric learning on manifold. - Hong Shao; Shuang Chen 006; Jieyi Zhao; Wen-cheng Cui; Tianshu Yu 001 (Frontiers Inf. Technol. Electron. Eng., 2015)

Enhancing scene parsing by transferring structures via efficient low-rank graph matching. - Tianshu Yu 001; Ruisheng Wang (SIGSPATIAL/GIS, 2016)

Graph matching with low-rank regularization. - Tianshu Yu 001; Ruisheng Wang (WACV, 2016)

Scene parsing using graph matching on street-view data. - Tianshu Yu 001; Ruisheng Wang (Comput. Vis. Image Underst., 2016)

Simultaneous Event Localization and Recognition in Surveillance Video. - Yikang Li 001; Tianshu Yu 001; Baoxin Li (AVSS, 2018)

Joint Cuts and Matching of Partitions in One Graph. - Tianshu Yu 001; Junchi Yan; Jieyi Zhao; Baoxin Li (CVPR, 2018)

Incremental Multi-graph Matching via Diversity and Randomness Based Graph Clustering. - Tianshu Yu 001; Junchi Yan; Wei Liu 005; Baoxin Li (ECCV (13), 2018)

Generalizing Graph Matching beyond Quadratic Assignment Model. - Tianshu Yu 001; Junchi Yan; Yilin Wang 002; Wei Liu 005; Baoxin Li (NeurIPS, 2018)

Weakly Supervised Attention Learning for Textual Phrases Grounding. - Zhiyuan Fang; Shu Kong; Tianshu Yu 001; Yezhou Yang (CoRR, 2018)

Plan-Recognition-Driven Attention Modeling for Visual Recognition. - Yantian Zha; Yikang Li 001; Tianshu Yu 001; Subbarao Kambhampati; Baoxin Li (CoRR, 2018)

Determinant Regularization for Gradient-Efficient Graph Matching. - Tianshu Yu 001; Junchi Yan; Baoxin Li (CVPR, 2020)

RhyRNN: Rhythmic RNN for Recognizing Events in Long and Complex Videos. - Tianshu Yu 001; Yikang Li 001; Baoxin Li (ECCV (10), 2020)

Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient. - Tianshu Yu 001; Yikang Li 001; Baoxin Li (ICLR, 2020)

Learning deep graph matching with channel-independent embedding and Hungarian attention. - Tianshu Yu 001; Runzhong Wang; Junchi Yan; Baoxin Li (ICLR, 2020)

Recognizing Video Events with Varying Rhythms. - Yikang Li 001; Tianshu Yu 001; Baoxin Li (CoRR, 2020)

Variational Wasserstein Barycenters for Geometric Clustering. - Liang Mi; Tianshu Yu 001; José Bento 001; Wen Zhang 010; Baoxin Li; Yalin Wang 001 (CoRR, 2020)

Combinatorial Learning of Graph Edit Distance via Dynamic Embedding. - Runzhong Wang; Tianqi Zhang; Tianshu Yu 001; Junchi Yan; Xiaokang Yang 001 (CVPR, 2021)

Deep Latent Graph Matching. - Tianshu Yu 001; Runzhong Wang; Junchi Yan; Baoxin Li (ICML, 2021)

Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis. - Haoyu Zhang 001; Yu Wang 246; Guanghao Yin; Kejun Liu; Yuanyuan Liu 004; Tianshu Yu 001 (EMNLP, 2023)

Learning to Decouple Complex Systems. - Zihan Zhou 024; Tianshu Yu 001 (ICML, 2023)

Efficient Training of Multi-task Neural Solver with Multi-armed Bandits. - Chenguang Wang 011; Tianshu Yu 001 (CoRR, 2023)

A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem. - Zhang-Hua Fu; Sipeng Sun; Jintong Ren; Tianshu Yu 001; Haoyu Zhang 001; Yuanyuan Liu 004; Lingxiao Huang; Xiang Yan; Pinyan Lu (CoRR, 2023)

Molecular Conformation Generation via Shifting Scores. - Zihan Zhou 024; Ruiying Liu; Chaolong Ying; Ruimao Zhang; Tianshu Yu 001 (CoRR, 2023)

Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring. - Shanchao Yang; Kaili Ma 001; Baoxiang Wang 001; Tianshu Yu 001; Hongyuan Zha (Trans. Mach. Learn. Res., 2023)

Single Cell Gene Expression Prediction via Prototype-based Proximal Neural Factorization. - Xiaozhuang Song; Xu Liao; Hangting Ye; Yaoyao Xu; Wei Fan 010; Jin Liu; Tianshu Yu 001 (BIBM, 2024)

Neural Enhanced Variational Bayesian Inference on Graphs for Localized Statistical Channel Modeling. - Yiheng Wang; Shutao Zhang; Ye Xue; Tianshu Yu 001; Qingjiang Shi; Tsung-Hui Chang (ICC, 2024)

Boosting Graph Pooling with Persistent Homology. - Chaolong Ying; Xinjian Zhao; Tianshu Yu 001 (NeurIPS, 2024)

Towards Robust Multimodal Sentiment Analysis with Incomplete Data. - Haoyu Zhang 001; Wenbin Wang 001; Tianshu Yu 001 (NeurIPS, 2024)

Boosting Protein Language Models with Negative Sample Mining. - Yaoyao Xu; Xinjian Zhao; Xiaozhuang Song; Benyou Wang; Tianshu Yu 001 (ECML/PKDD (10), 2024)

Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory. - Weichen Zhao; Chenguang Wang 011; Xinyan Wang 004; Congying Han; Tiande Guo; Tianshu Yu 001 (CoRR, 2024)

Towards Principled Task Grouping for Multi-Task Learning. - Chenguang Wang 011; Xuanhao Pan; Tianshu Yu 001 (CoRR, 2024)

Graph Learning with Distributional Edge Layouts. - Xinjian Zhao; Chaolong Ying; Tianshu Yu 001 (CoRR, 2024)

On Diffusion Process in SE(3)-invariant Space. - Zihan Zhou 024; Ruiying Liu; Jiachen Zheng; Xiaoxue Wang; Tianshu Yu 001 (CoRR, 2024)

Do spectral cues matter in contrast-based graph self-supervised learning? - Xiangru Jian; Xinjian Zhao; Wei Pang; Chaolong Ying; Yimu Wang; Yaoyao Xu; Tianshu Yu 001 (CoRR, 2024)

Rethinking the "Heatmap + Monte Carlo Tree Search" Paradigm for Solving Large Scale TSP. - Xuanhao Pan; Chenguang Wang 011; Chaolong Ying; Ye Xue; Tianshu Yu 001 (CoRR, 2024)

NeuroLifting: Neural Inference on Markov Random Fields at Scale. - Yaomin Wang; Chaolong Ying; Xiaodong Luo; Tianshu Yu 001 (CoRR, 2024)

ASP: Learn a Universal Neural Solver! - Chenguang Wang 011; Zhouliang Yu; Stephen McAleer; Tianshu Yu 001; Yaodong Yang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Efficient Neural Collaborative Search for Pickup and Delivery Problems. - Detian Kong; Yining Ma 001; Zhiguang Cao; Tianshu Yu 001; Jianhua Xiao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Enhancing Generalizability in Molecular Conformation Generation with METRIZATION-Informed Geometric Diffusion Pretraining. - Xiaozhuang Song; Yuzhao Tu; Hangting Ye; Wei Fan 010; Qingquan Zhang; Xiaoxue Wang; Tianshu Yu 001 (AAAI, 2025)

ReKG-MCTS: Reinforcing LLM Reasoning on Knowledge Graphs via Training-Free Monte Carlo Tree Search. - Xiaozhuang Song; Shufei Zhang; Tianshu Yu 001 (ACL (Findings), 2025)

Generating Physical Dynamics under Priors. - Zihan Zhou 024; Xiaoxue Wang; Tianshu Yu 001 (ICLR, 2025)

Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory. - Weichen Zhao; Chenguang Wang 001; Xinyan Wang 004; Congying Han; Tiande Guo; Tianshu Yu 001 (KDD (1), 2025)

Graph Learning with Distributional Edge Layouts. - Xinjian Zhao; Chaolong Ying; Yaoyao Xu; Tianshu Yu 001 (KDD (1), 2025)

Efficient Training of Multi-task Neural Solver for Combinatorial Optimization. - Chenguang Wang 011; Zhang-Hua Fu; Pinyan Lu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)

Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning. - Xiangru Jian; Xinjian Zhao; Wei Pang; Chaolong Ying; Yimu Wang; Yaoyao Xu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)

Enhancing Molecular Conformer Generation via Fragment- Augmented Diffusion Pretraining. - Xiaozhuang Song; Yuzhao Tu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)

GraphOmni: A Comprehensive and Extendable Benchmark Framework for Large Language Models on Graph-theoretic Tasks. - Hao Xu; Xiangru Jian; Xinjian Zhao; Wei Pang; Chao Zhang 045; Suyuchen Wang; Qixin Zhang 001; Joao Monteiro; Qiuzhuang Sun; Tianshu Yu 001 (CoRR, 2025)

Neural Graduated Assignment for Maximum Common Edge Subgraphs. - Chaolong Ying; Yingqi Ruan; Xuemin Chen; Yaomin Wang; Tianshu Yu 001 (CoRR, 2025)

SDRNET: Stacked Deep Residual Network for Accurate Semantic Segmentation of Fine-Resolution Remotely Sensed Images. - Naftaly Wambugu; Ruisheng Wang; Bo Guo; Tianshu Yu 001; Sheng Xu; Mohammed A. M. Elhassan (CoRR, 2025)