On DE: Its Nature and Features. - Huibin Zhuang; Wenlei Shi; Meihua Wang; Zhenqian Liu (CLSW, 2013)

Enabling RFID-Based Tracking for Multi-Objects with Visual Aids: A Calibration-Free Solution. - Chunhui Duan; Wenlei Shi; Fan Dang 001; Xuan Ding (INFOCOM, 2020)

Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. - Wenlei Shi; Xinran Wei; Jia Zhang 004; Xiaoyuan Ni; Arthur Jiang; Jiang Bian 002; Tie-Yan Liu (AAMAS, 2021)

Application of Deep Learning in Financial Management Evaluation. - Wenlei Shi; Lei Xu; Dongli Peng (Sci. Program., 2021)

LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. - Wenlei Shi; Xinquan Huang; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (CoRR, 2022)

Learning Physics-Informed Neural Networks without Stacked Back-propagation. - Di He 001; Shanda Li; Wenlei Shi; Xiaotian Gao; Jia Zhang 004; Jiang Bian 002; Liwei Wang 001; Tie-Yan Liu (AISTATS, 2023)

NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition. - Xinquan Huang; Wenlei Shi; Qi Meng; Yue Wang 017; Xiaotian Gao; Jia Zhang 004; Tie-Yan Liu (ICML, 2023)

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2023)

Process Supervision-Guided Policy Optimization for Code Generation. - Ning Dai; Zheng Wu; Renjie Zheng; Ziyun Wei; Wenlei Shi; Xing Jin; Guanlin Liu; Chen Dun; Liang Huang 001; Lin Yan (CoRR, 2024)

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. - Xinquan Huang; Wenlei Shi; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (Neural Networks, 2024)

Flaming-hot Initiation with Regular Execution Sampling for Large Language Models. - Weizhe Chen 001; Zhicheng Zhang; Guanlin Liu; Renjie Zheng; Wenlei Shi; Chen Dun; Zheng Wu; Xing Jin; Lin Yan (NAACL (Findings), 2025)

Heimdall: test-time scaling on the generative verification. - Wenlei Shi; Xing Jin (CoRR, 2025)

Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving. - Luoxin Chen; Jinming Gu; Liankai Huang; Wenhao Huang 001; Zhicheng Jiang; Allan Jie; Xiaoran Jin; Xing Jin; Chenggang Li; Kaijing Ma; Cheng Ren; Jiawei Shen; et al. (CoRR, 2025)