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ORCIDTianshu Yu 0001
Person information
- affiliation: Chinese University of Hong Kong, Shenzhen, China
- affiliation (PhD 2021): Arizona State University, Tempe, AZ, USA
- affiliation (former): University of Calgary, Department of Geomatics Engineering, AB, Canada
Other persons with the same name
- Tianshu Yu 0002
![[0009-0001-9613-5123]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0001-9613-5123")
— Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, China - Tianshu Yu 0003 — Beihang University, School of Computer Science and Engineering, State Key Laboratory of Virtual Reality Technology and Systems, Beijing, China
- Tianshu Yu 0004 — Tsinghua University, Conversational Artificial Intelligence (CoAI), Beijing, China (and 1 more)
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2020 – today
- 2026
[j9]Libin Lan, Lu Jiang, Tianshu Yu, Xiaojuan Liu, Zhongshi He:
FullTransNet: Full Transformer With Local-Global Attention for Video Summarization. IEEE Trans. Emerg. Top. Comput. Intell. 10(2): 1185-1200 (2026)- [c27]Xiaozhuang Song, Tianshu Yu:
Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics. AAAI 2026: 1024-1032 - [i36]Huan Zhang, Yizhan Li, Wenhao Huang, Ziyu Hou, Yu Song, Xuye Liu, Farshid Effaty, Jinya Jiang, Sifan Wu, Qianggang Ding, Izumi Takahara, Leonard R. MacGillivray, Teruyasu Mizoguchi, Tianshu Yu, Lizi Liao, Yuyu Luo, Yu Rong, Jia Li, Ying Diao, Heng Ji, Bang Liu:
Towards Agentic Intelligence for Materials Science. CoRR abs/2602.00169 (2026) - [i35]Haoyu Zhang, Zhipeng Li, Yiwen Guo, Tianshu Yu:
Ex-Omni: Enabling 3D Facial Animation Generation for Omni-modal Large Language Models. CoRR abs/2602.07106 (2026) - [i34]Chenguang Wang, Zihan Zhou, Lei Bai, Tianshu Yu:
Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching. CoRR abs/2602.13136 (2026) - 2025
- [j8]Chenguang Wang, Zhang-Hua Fu, Pinyan Lu, Tianshu Yu:
Efficient Training of Multi-task Neural Solver for Combinatorial Optimization. Trans. Mach. Learn. Res. 2025 (2025) - [j7]Xiangru Jian, Xinjian Zhao, Wei Pang, Chaolong Ying, Yimu Wang, Yaoyao Xu, Tianshu Yu:
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning. Trans. Mach. Learn. Res. 2025 (2025) - [j6]Xiaozhuang Song, Yuzhao Tu, Tianshu Yu:
Enhancing Molecular Conformer Generation via Fragment- Augmented Diffusion Pretraining. Trans. Mach. Learn. Res. 2025 (2025) - [c26]Xiaozhuang Song, Yuzhao Tu, Hangting Ye, Wei Fan, Qingquan Zhang, Xiaoxue Wang, Tianshu Yu:
Enhancing Generalizability in Molecular Conformation Generation with METRIZATION-Informed Geometric Diffusion Pretraining. AAAI 2025: 755-763 - [c25]Xiaozhuang Song, Shufei Zhang, Tianshu Yu:
ReKG-MCTS: Reinforcing LLM Reasoning on Knowledge Graphs via Training-Free Monte Carlo Tree Search. ACL (Findings) 2025: 9288-9306 - [c24]Zihan Zhou, Xiaoxue Wang, Tianshu Yu:
Generating Physical Dynamics under Priors. ICLR 2025 - [c23]Chenguang Wang, Kaiyuan Cui, Weichen Zhao, Tianshu Yu:
Sampling from Binary Quadratic Distributions via Stochastic Localization. ICML 2025 - [c22]Weichen Zhao, Chenguang Wang, Xinyan Wang, Congying Han, Tiande Guo, Tianshu Yu:
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory. KDD (1) 2025: 2043-2054 - [c21]Xinjian Zhao, Chaolong Ying, Yaoyao Xu, Tianshu Yu:
Graph Learning with Distributional Edge Layouts. KDD (1) 2025: 2055-2066 - [i33]Hao Xu, Xiangru Jian, Xinjian Zhao, Wei Pang, Chao Zhang, Suyuchen Wang, Qixin Zhang, Joao Monteiro, Qiuzhuang Sun, Tianshu Yu:
GraphOmni: A Comprehensive and Extendable Benchmark Framework for Large Language Models on Graph-theoretic Tasks. CoRR abs/2504.12764 (2025) - [i32]Chaolong Ying, Yingqi Ruan, Xuemin Chen, Yaomin Wang, Tianshu Yu:
Neural Graduated Assignment for Maximum Common Edge Subgraphs. CoRR abs/2505.12325 (2025) - [i31]Naftaly Wambugu, Ruisheng Wang, Bo Guo, Tianshu Yu, Sheng Xu, Mohammed A. M. Elhassan:
SDRNET: Stacked Deep Residual Network for Accurate Semantic Segmentation of Fine-Resolution Remotely Sensed Images. CoRR abs/2506.21945 (2025) - [i30]Chaolong Ying, Yinan Zhang, Lei Zhang, Jiazhuang Wang, Shujun Jia, Tianshu Yu:
UM3: Unsupervised Map to Map Matching. CoRR abs/2508.16874 (2025) - [i29]Zihan Zhou, Chenguang Wang, Hongyi Ye, Yongtao Guan, Tianshu Yu:
Incomplete Data, Complete Dynamics: A Diffusion Approach. CoRR abs/2509.20098 (2025) - [i28]Xiaozhuang Song, Xuanhao Pan, Xinjian Zhao, Hangting Ye, Shufei Zhang, Jian Tang, Tianshu Yu:
AOT*: Efficient Synthesis Planning via LLM-Empowered AND-OR Tree Search. CoRR abs/2509.20988 (2025) - [i27]Weida Wang, Benteng Chen, Di Zhang, Wanhao Liu, Shuchen Pu, Ben Gao, Jin Zeng, Xiaoyong Wei, Tianshu Yu, Shuzhou Sun, Tianfan Fu, Wanli Ouyang, Lei Bai, Jiatong Li, Zifu Wang, Yuqiang Li, Shufei Zhang:
Chem-R: Learning to Reason as a Chemist. CoRR abs/2510.16880 (2025) - [i26]Xinjian Zhao, Wei Pang, Zhongkai Xue, Xiangru Jian, Lei Zhang, Yaoyao Xu, Xiaozhuang Song, Shu Wu, Tianshu Yu:
The Underappreciated Power of Vision Models for Graph Structural Understanding. CoRR abs/2510.24788 (2025) - [i25]Yaoyao Xu, Di Wang, Zihan Zhou, Tianshu Yu, Mingchen Chen:
TEMPO: Temporal Multi-scale Autoregressive Generation of Protein Conformational Ensembles. CoRR abs/2511.05510 (2025) - [i24]Ruiying Liu, Yuanzhi Liang, Haibin Huang, Tianshu Yu, Chi Zhang:
Learning What to Trust: Bayesian Prior-Guided Optimization for Visual Generation. CoRR abs/2511.18919 (2025) - 2024
- [j5]Chenguang Wang, Zhouliang Yu, Stephen McAleer, Tianshu Yu, Yaodong Yang:
ASP: Learn a Universal Neural Solver! IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4102-4114 (2024) - [j4]Detian Kong, Yining Ma, Zhiguang Cao, Tianshu Yu, Jianhua Xiao:
Efficient Neural Collaborative Search for Pickup and Delivery Problems. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11019-11034 (2024) - [c20]Xiaozhuang Song, Xu Liao, Hangting Ye, Yaoyao Xu, Wei Fan, Jin Liu, Tianshu Yu:
Single Cell Gene Expression Prediction via Prototype-based Proximal Neural Factorization. BIBM 2024: 1666-1673 - [c19]Yiheng Wang, Shutao Zhang, Ye Xue, Tianshu Yu, Qingjiang Shi, Tsung-Hui Chang:
Neural Enhanced Variational Bayesian Inference on Graphs for Localized Statistical Channel Modeling. ICC 2024: 342-347 - [c18]Chaolong Ying, Xinjian Zhao, Tianshu Yu:
Boosting Graph Pooling with Persistent Homology. NeurIPS 2024 - [c17]Haoyu Zhang, Wenbin Wang, Tianshu Yu:
Towards Robust Multimodal Sentiment Analysis with Incomplete Data. NeurIPS 2024 - [c16]Yaoyao Xu, Xinjian Zhao, Xiaozhuang Song, Benyou Wang, Tianshu Yu:
Boosting Protein Language Models with Negative Sample Mining. ECML/PKDD (10) 2024: 199-214 - [i23]Weichen Zhao, Chenguang Wang, Xinyan Wang, Congying Han, Tiande Guo, Tianshu Yu:
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory. CoRR abs/2402.15326 (2024) - [i22]Chenguang Wang, Xuanhao Pan, Tianshu Yu:
Towards Principled Task Grouping for Multi-Task Learning. CoRR abs/2402.15328 (2024) - [i21]Chaolong Ying, Xinjian Zhao, Tianshu Yu:
Boosting Graph Pooling with Persistent Homology. CoRR abs/2402.16346 (2024) - [i20]Xinjian Zhao, Chaolong Ying, Tianshu Yu:
Graph Learning with Distributional Edge Layouts. CoRR abs/2402.16402 (2024) - [i19]Zihan Zhou, Ruiying Liu, Jiachen Zheng, Xiaoxue Wang, Tianshu Yu:
On Diffusion Process in SE(3)-invariant Space. CoRR abs/2403.01430 (2024) - [i18]Yaoyao Xu, Xinjian Zhao, Xiaozhuang Song, Benyou Wang, Tianshu Yu:
Boosting Protein Language Models with Negative Sample Mining. CoRR abs/2405.17902 (2024) - [i17]Xiangru Jian, Xinjian Zhao, Wei Pang, Chaolong Ying, Yimu Wang, Yaoyao Xu, Tianshu Yu:
Do spectral cues matter in contrast-based graph self-supervised learning? CoRR abs/2405.19600 (2024) - [i16]Zihan Zhou, Xiaoxue Wang, Tianshu Yu:
Generating Physical Dynamics under Priors. CoRR abs/2409.00730 (2024) - [i15]Haoyu Zhang, Wenbin Wang, Tianshu Yu:
Towards Robust Multimodal Sentiment Analysis with Incomplete Data. CoRR abs/2409.20012 (2024) - [i14]Xuanhao Pan, Chenguang Wang, Chaolong Ying, Ye Xue, Tianshu Yu:
Rethinking the "Heatmap + Monte Carlo Tree Search" Paradigm for Solving Large Scale TSP. CoRR abs/2411.09238 (2024) - [i13]Yaomin Wang, Chaolong Ying, Xiaodong Luo, Tianshu Yu:
NeuroLifting: Neural Inference on Markov Random Fields at Scale. CoRR abs/2411.18954 (2024) - 2023
- [j3]Shanchao Yang, Kaili Ma, Baoxiang Wang, Tianshu Yu, Hongyuan Zha:
Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring. Trans. Mach. Learn. Res. 2023 (2023) - [c15]Haoyu Zhang, Yu Wang, Guanghao Yin, Kejun Liu, Yuanyuan Liu, Tianshu Yu:
Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis. EMNLP 2023: 756-767 - [c14]Zihan Zhou, Tianshu Yu:
Learning to Decouple Complex Systems. ICML 2023: 42810-42828 - [i12]Zihan Zhou, Tianshu Yu:
Learning to Decouple Complex Systems. CoRR abs/2302.01581 (2023) - [i11]Chenguang Wang, Zhouliang Yu, Stephen McAleer, Tianshu Yu, Yaodong Yang:
ASP: Learn a Universal Neural Solver! CoRR abs/2303.00466 (2023) - [i10]Chenguang Wang, Tianshu Yu:
Efficient Training of Multi-task Neural Solver with Multi-armed Bandits. CoRR abs/2305.06361 (2023) - [i9]Zhang-Hua Fu, Sipeng Sun, Jintong Ren, Tianshu Yu, Haoyu Zhang, Yuanyuan Liu, Lingxiao Huang, Xiang Yan, Pinyan Lu:
A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem. CoRR abs/2308.04639 (2023) - [i8]Zihan Zhou, Ruiying Liu, Chaolong Ying, Ruimao Zhang, Tianshu Yu:
Molecular Conformation Generation via Shifting Scores. CoRR abs/2309.09985 (2023) - [i7]Haoyu Zhang, Yu Wang, Guanghao Yin, Kejun Liu, Yuanyuan Liu, Tianshu Yu:
Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis. CoRR abs/2310.05804 (2023) - 2021
- [c13]Runzhong Wang, Tianqi Zhang, Tianshu Yu, Junchi Yan, Xiaokang Yang:
Combinatorial Learning of Graph Edit Distance via Dynamic Embedding. CVPR 2021: 5241-5250 - [c12]Tianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li:
Deep Latent Graph Matching. ICML 2021: 12187-12197 - 2020
- [c11]Tianshu Yu, Junchi Yan, Baoxin Li:
Determinant Regularization for Gradient-Efficient Graph Matching. CVPR 2020: 7121-7130 - [c10]Tianshu Yu, Yikang Li, Baoxin Li:
RhyRNN: Rhythmic RNN for Recognizing Events in Long and Complex Videos. ECCV (10) 2020: 127-144 - [c9]Tianshu Yu, Yikang Li, Baoxin Li:
Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient. ICLR 2020 - [c8]Tianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li:
Learning deep graph matching with channel-independent embedding and Hungarian attention. ICLR 2020 - [i6]Yikang Li, Tianshu Yu, Baoxin Li:
Recognizing Video Events with Varying Rhythms. CoRR abs/2001.05060 (2020) - [i5]Liang Mi, Tianshu Yu, José Bento, Wen Zhang, Baoxin Li, Yalin Wang:
Variational Wasserstein Barycenters for Geometric Clustering. CoRR abs/2002.10543 (2020) - [i4]Runzhong Wang, Tianqi Zhang, Tianshu Yu, Junchi Yan, Xiaokang Yang:
Combinatorial Learning of Graph Edit Distance via Dynamic Embedding. CoRR abs/2011.15039 (2020)
2010 – 2019
- 2018
- [c7]Yikang Li, Tianshu Yu, Baoxin Li:
Simultaneous Event Localization and Recognition in Surveillance Video. AVSS 2018: 1-6 - [c6]Tianshu Yu, Junchi Yan, Jieyi Zhao, Baoxin Li:
Joint Cuts and Matching of Partitions in One Graph. CVPR 2018: 705-713 - [c5]Tianshu Yu, Junchi Yan, Wei Liu, Baoxin Li:
Incremental Multi-graph Matching via Diversity and Randomness Based Graph Clustering. ECCV (13) 2018: 142-158 - [c4]Tianshu Yu, Junchi Yan, Yilin Wang, Wei Liu, Baoxin Li:
Generalizing Graph Matching beyond Quadratic Assignment Model. NeurIPS 2018: 861-871 - [i3]Zhiyuan Fang, Shu Kong, Tianshu Yu, Yezhou Yang:
Weakly Supervised Attention Learning for Textual Phrases Grounding. CoRR abs/1805.00545 (2018) - [i2]Yantian Zha, Yikang Li, Tianshu Yu, Subbarao Kambhampati, Baoxin Li:
Plan-Recognition-Driven Attention Modeling for Visual Recognition. CoRR abs/1812.00301 (2018) - 2017
- [i1]Tianshu Yu, Junchi Yan, Jieyi Zhao, Baoxin Li:
Joint Cuts and Matching of Partitions in One Graph. CoRR abs/1711.09584 (2017) - 2016
- [j2]Tianshu Yu, Ruisheng Wang:
Scene parsing using graph matching on street-view data. Comput. Vis. Image Underst. 145: 70-80 (2016) - [c3]Tianshu Yu, Ruisheng Wang:
Enhancing scene parsing by transferring structures via efficient low-rank graph matching. SIGSPATIAL/GIS 2016: 22:1-22:9 - [c2]Tianshu Yu, Ruisheng Wang:
Graph matching with low-rank regularization. WACV 2016: 1-9 - 2015
- [j1]Hong Shao, Shuang Chen, Jieyi Zhao, Wen-cheng Cui, Tianshu Yu:
Face recognition based on subset selection via metric learning on manifold. Frontiers Inf. Technol. Electron. Eng. 16(12): 1046-1058 (2015) - 2012
- [c1]Wen-cheng Cui, Tianshu Yu, Lijie Ren, Hong Shao:
Ribs segmentation based on image fusion and wavelet de-noising. BMEI 2012: 362-366
Coauthor Index
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