M-Statistic for Kernel Change-Point Detection. - Shuang Li 002; Yao Xie 002; Hanjun Dai; Le Song (NIPS, 2015)

Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression. - Yu-Ying Liu; Shuang Li 002; Fuxin Li; Le Song; James M. Rehg (NIPS, 2015)

Co-evolutionary Dynamics of Information Diffusion and Network Structure. - Mehrdad Farajtabar; Manuel Gomez-Rodriguez; Yichen Wang 001; Shuang Li 002; Hongyuan Zha; Le Song (WWW (Companion Volume), 2015)

Online seismic event picking via sequential change-point detection. - Shuang Li 002; Yang Cao 013; Christina Leamon; Yao Xie 002; Lei Shi 014; Wen-Zhan Song 001 (Allerton, 2016)

Detecting weak changes in dynamic events over networks. - Shuang Li 002; Yao Xie 002; Mehrdad Farajtabar; Le Song (CoRR, 2016)

Data-Driven Threshold Machine: Scan Statistics, Change-Point Detection, and Extreme Bandits. - Shuang Li 002; Yao Xie 002; Le Song (CoRR, 2016)

Learning Continuous-Time Hidden Markov Models for Event Data. - Yu-Ying Liu; Alexander Moreno; Shuang Li 002; Fuxin Li; Le Song; James M. Rehg (Mobile Health - Sensors, Analytic Methods, and Applications, 2017)

Recurrent Hidden Semi-Markov Model. - Hanjun Dai; Bo Dai 001; Yan-Ming Zhang; Shuang Li 002; Le Song (ICLR (Poster), 2017)

Fake News Mitigation via Point Process Based Intervention. - Mehrdad Farajtabar; Jiachen Yang; Xiaojing Ye; Huan Xu; Rakshit Trivedi; Elias B. Khalil; Shuang Li 002; Le Song; Hongyuan Zha (ICML, 2017)

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution. - Mehrdad Farajtabar; Yichen Wang 001; Manuel Gomez-Rodriguez; Shuang Li 002; Hongyuan Zha; Le Song (J. Mach. Learn. Res., 2017)

Detecting Changes in Dynamic Events Over Networks. - Shuang Li 002; Yao Xie 002; Mehrdad Farajtabar; Apurv Verma; Le Song (IEEE Trans. Signal Inf. Process. over Networks, 2017)

Learning Temporal Point Processes via Reinforcement Learning. - Shuang Li 002; Shuai Xiao; Shixiang Zhu; Nan Du 002; Yao Xie 002; Le Song (NeurIPS, 2018)

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. - Mehrdad Farajtabar; Manuel Gomez-Rodriguez; Yichen Wang 001; Shuang Li 002; Hongyuan Zha; Le Song (WWW (Companion Volume), 2018)

Neural Model-Based Reinforcement Learning for Recommendation. - Xinshi Chen; Shuang Li 002; Hui Li 061; Shaohua Jiang; Yuan Qi 001; Le Song (CoRR, 2018)

Generative Adversarial User Model for Reinforcement Learning Based Recommendation System. - Xinshi Chen; Shuang Li 002; Hui Li 061; Shaohua Jiang; Yuan Qi 001; Le Song (ICML, 2019)

Reinforcement Learning of Spatio-Temporal Point Processes. - Shixiang Zhu; Shuang Li 002; Yao Xie 002 (CoRR, 2019)

Statistical Inference, Modeling, and Learning of Point Processes. - Shuang Li 002 (2019)

Continuous-Time Dynamic Graph Learning via Neural Interaction Processes. - Xiaofu Chang; Xuqin Liu; Jianfeng Wen; Shuang Li 002; Yanming Fang; Le Song; Yuan Qi 001 (CIKM, 2020)

Temporal Logic Point Processes. - Shuang Li 002; Lu Wang 008; Ruizhi Zhang; Xiaofu Chang; Xuqin Liu; Yao Xie 002; Yuan Qi 001; Le Song (ICML, 2020)

TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning. - Lu Wang 029; Xiaofu Chang; Shuang Li 002; Yunfei Chu; Hui Li 061; Wei Zhang 012; Xiaofeng He; Le Song; Jingren Zhou 001; Hongxia Yang (CoRR, 2021)

Understanding the Spread of COVID-19 Epidemic: A Spatio-Temporal Point Process View. - Shuang Li 002; Lu Wang 008; Xinyun Chen; Yixiang Fang; Yan Song 003 (CoRR, 2021)

A Note on General Statistics of Publicly Accessible Knowledge Bases. - Feixiang Wang; Yixiang Fang; Yan Song 003; Shuang Li 002; Xinyun Chen (CoRR, 2021)

Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling. - Yu-Ying Liu; Alexander Moreno; Maxwell A. Xu; Shuang Li 002; Jena C. McDaniel; Nancy C. Brady; Agata Rozga; Fuxin Li; Le Song; James M. Rehg (CoRR, 2021)

Explaining Point Processes by Learning Interpretable Temporal Logic Rules. - Shuang Li 002; Mingquan Feng; Lu Wang 029; Abdelmajid Essofi; Yufeng Cao; Junchi Yan; Le Song (ICLR, 2022)

Learning Temporal Rules from Noisy Timeseries Data. - Karan Samel; Zelin Zhao; Binghong Chen; Shuang Li 002; Dharmashankar Subramanian; Irfan Essa; Le Song (CoRR, 2022)

Imitation Learning of Neural Spatio-Temporal Point Processes. - Shixiang Zhu; Shuang Li 002; Zhigang Peng; Yao Xie 002 (IEEE Trans. Knowl. Data Eng., 2022)

Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions. - Chengzhi Cao; Chao Yang; Ruimao Zhang; Shuang Li 002 (NeurIPS, 2023)

Introspective Tips: Large Language Model for In-Context Decision Making. - Liting Chen; Lu Wang 029; Hang Dong 004; Yali Du 001; Jie Yan; Fangkai Yang; Shuang Li 002; Pu Zhao 004; Si Qin; Saravan Rajmohan; Qingwei Lin; Dongmei Zhang 001 (CoRR, 2023)

Reinforcement Logic Rule Learning for Temporal Point Processes. - Chao Yang; Lu Wang 029; Kun Gao 003; Shuang Li 002 (CoRR, 2023)

Hawkes Processes with Delayed Granger Causality. - Chao Yang; Hengyuan Miao; Shuang Li 002 (CoRR, 2023)

Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation. - Yiling Kuang; Chao Yang; Yang Yang; Shuang Li 002 (AISTATS, 2024)

Enhancing Human-AI Collaboration Through Logic-Guided Reasoning. - Chengzhi Cao; Yinghao Fu; Sheng Xu; Ruimao Zhang; Shuang Li 002 (ICLR, 2024)

Amortized Network Intervention to Steer the Excitatory Point Processes. - Zitao Song; Wendi Ren; Shuang Li 002 (ICLR, 2024)

Latent Logic Tree Extraction for Event Sequence Explanation from LLMs. - Zitao Song; Chao Yang; Chaojie Wang 001; Bo An 001; Shuang Li 002 (ICML, 2024)

Neuro-Symbolic Temporal Point Processes. - Yang Yang; Chao Yang; Boyang Li; Yinghao Fu; Shuang Li 002 (ICML, 2024)

Logic-Logit: A Logic-Based Approach to Choice Modeling. - Shuhan Zhang; Wendi Ren; Shuang Li 002 (ICLR, 2025)

Reproducing Kernel Hilbert Space Choice Model. - Yiqi Yang; Zhi Wang; Rui Gao 001; Shuang Li 002 (EC, 2025)

Flow-Based Delayed Hawkes Process. - Chao Yang; Wendi Ren; Shuang Li 002 (UAI, 2025)