Interpretable Spatial-Temporal Attention Graph Convolution Network for Service Part Hierarchical Demand Forecast. - Wenli Ouyang; Yahong Zhang; Mingda Zhu; Xiuling Zhang; Hongye Chen; Yinghao Ren; Wei Fan (NLPCC (2), 2019)

A new approach to forecast service parts demand by integrating user preferences into multi-objective optimization. - Wenli Ouyang (CoRR, 2019)

Interpretable Multi-Scale Neural Network for Granger Causality Discovery. - Chenchen Fan; Yixin Wang; Yahong Zhang; Wenli Ouyang (ICASSP, 2023)

Long-Tailed Recognition with Causal Invariant Transformation. - Yahong Zhang; Sheng Shi; Chenchen Fan; Yixin Wang; Wenli Ouyang; WeiFan; Jianping Fan 007 (ICASSP, 2023)

Learnable Query Guided Representation Learning for Treatment Effect Estimation. - Chenchen Fan; Yixin Wang; Yahong Zhang; Wenli Ouyang; Sheng Shi; Wei Fan; Jianping Fan 007 (IJCNN, 2023)

Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach. - Changwen Zhang; Wenli Ouyang; Hao Yuan 002; Liming Gong; Yong Sun; Ziao Guo; Zhichen Dong; Junchi Yan (ICLR, 2024)

ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation. - Ziao Guo; Yang Li 197; Chang Liu 021; Wenli Ouyang; Junchi Yan (ICML, 2024)

MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness. - Yahong Zhang; Chenchen Fan; Donghui Chen; Congrui Li; Wenli Ouyang; Mingda Zhu; Junchi Yan (ICML, 2024)

Approximation algorithms for mixed batch scheduling on parallel machines. - Dong Wang; Kan Fang; Wenchang Luo; Wenli Ouyang (J. Oper. Res. Soc., 2024)

BTBS-LNS: Binarized-Tightening, Branch and Search on Learning LNS Policies for MIP. - Hao Yuan 002; Wenli Ouyang; Changwen Zhang; Yong Sun; Liming Gong; Junchi Yan (ICLR, 2025)