Kexin Zhang - RankMe

27 papers A* 1A 3Misc 2Journal 19Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Survey of Deep Graph Learning under Distribution Shifts: From Graph Out-of-Distribution Generalization to Adaptation. ACM Trans. Knowl. Discov. Data Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding
2026	J	`jnl`	From Observations to States: Latent Time Series Forecasting. CoRR Jie Yang, Yifan Hu, Yuante Li, Kexin Zhang, Kaize Ding, Philip S. Yu
2026	J	`jnl`	Parallel Complex Diffusion for Scalable Time Series Generation. CoRR Rongyao Cai, Yuxi Wan, Kexin Zhang, Ming Jin, Zhiqiang Ge, Qingsong Wen, Yong Liu
2025	J	`jnl`	A Survey of Large Language Models for Text-Guided Molecular Discovery: from Molecule Generation to Optimization. CoRR Ziqing Wang, Kexin Zhang, Zihan Zhao, Yibo Wen, Abhishek Pandey, Han Liu, Kaize Ding
2025	J	`jnl`	Adversarial Multimodal Contrastive Learning for Robust Industrial Fault Diagnosis. IEEE Trans. Instrum. Meas. Rongyao Cai, Kexin Zhang, Hanchen Tai, Yang Zhou, Yuanyuan Ding, Chunlin Zhou, Yong Liu
2025	—	`conf`	Combinatorial Optimization Perspective based Framework for Multi-behavior Recommendation. KDD (1) Chenhao Zhai, Chang Meng, Yu Yang, Kexin Zhang, Xuhao Zhao, Xiu Li
2025	J	`jnl`	Combinatorial Optimization Perspective based Framework for Multi-behavior Recommendation. CoRR Chenhao Zhai, Chang Meng, Yu Yang, Kexin Zhang, Xuhao Zhao, Xiu Li
2025	—	`conf`	Cross-Domain Conditional Diffusion Models for Time Series Imputation. ECML/PKDD (8) Kexin Zhang, Baoyu Jing, K. Selçuk Candan, Dawei Zhou, Qingsong Wen, Han Liu, Kaize Ding
2025	J	`jnl`	Cross-Domain Conditional Diffusion Models for Time Series Imputation. CoRR Kexin Zhang, Baoyu Jing, K. Selçuk Candan, Dawei Zhou, Qingsong Wen, Han Liu, Kaize Ding
2025	J	`jnl`	From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation. CoRR Rongyao Cai, Ming Jin, Qingsong Wen, Kexin Zhang
2025	A	`conf`	Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models. WSDM Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu
2025	J	`jnl`	Glocal Information Bottleneck for Time Series Imputation. CoRR Jie Yang, Kexin Zhang, Guibin Zhang, Philip S. Yu, Kaize Ding
2025	J	`jnl`	Revisiting Multivariate Time Series Forecasting with Missing Values. CoRR Jie Yang, Yifan Hu, Kexin Zhang, Luyang Niu, Yushun Dong, Philip S. Yu, Kaize Ding
2025	J	`jnl`	The Procrustean Bed of Time Series: The Optimization Bias of Point-wise Loss. CoRR Rongyao Cai, Yuxi Wan, Kexin Zhang, Ming Jin, Hao Wang, Zhiqiang Ge, Daoyi Dong, Yong Li, Qingsong Wen
2024	J	`jnl`	A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. CoRR Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding
2024	Misc	`conf`	DCS: Debiased Contrastive Learning with Weak Supervision for Time Series Classification. ICASSP Rongyao Cai, Linpeng Peng, Zhengming Lu, Kexin Zhang, Yong Liu
2024	J	`jnl`	Debiased Contrastive Learning With Supervision Guidance for Industrial Fault Detection. IEEE Trans. Ind. Informatics Rongyao Cai, Wang Gao, Linpeng Peng, Zhengming Lu, Kexin Zhang, Yong Liu
2024	J	`jnl`	Debiased Contrastive Learning for Time-Series Representation Learning and Fault Detection. IEEE Trans. Ind. Informatics Kexin Zhang, Rongyao Cai, Chunlin Zhou, Yong Liu
2024	J	`jnl`	Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models. CoRR Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue (Steve) Liu
2024	A	`conf`	IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation. WSDM Kexin Zhang, Yichao Wang, Xiu Li, Ruiming Tang, Rui Zhang
2024	J	`jnl`	Position Paper: What Can Large Language Models Tell Us about Time Series Analysis. CoRR Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen
2024	A*	`conf`	Position: What Can Large Language Models Tell Us about Time Series Analysis. ICML Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen
2024	J	`jnl`	Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. IEEE Trans. Pattern Anal. Mach. Intell. Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Y. Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
2024	Misc	`conf`	Skip-Step Contrastive Predictive Coding for Time Series Anomaly Detection. ICASSP Kexin Zhang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yong Liu
2023	J	`jnl`	Expert demonstrations guide reward decomposition for multi-agent cooperation. Neural Comput. Appl. Weiwei Liu, Jing Wei, Shanqi Liu, Yudi Ruan, Kexin Zhang, Yang Jiang, Yong Liu
2023	A	`conf`	HCL4QC: Incorporating Hierarchical Category Structures Into Contrastive Learning for E-commerce Query Classification. CIKM Lvxing Zhu, Kexin Zhang, Hao Chen, Chao Wei, Weiru Zhang, Haihong Tang, Xiu Li
2023	J	`jnl`	Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. CoRR Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan