Ramp Shape Optimum Design for Airplane Land-Based Ski-Jump Takeoff via NSGA II. - Xun-Kai Wei; Chong Duan; Ying Hong Li; Lirong Wu (ISDA (2), 2006)

SMS-based Mobile Recommendation System for Campus Recruitment in China. - Xiangpei Hu; Lirong Wu; Chao Li; Minfang Huang (ICMB, 2011)

A GAN-based Tunable Image Compression System. - Lirong Wu; Kejie Huang; Haibin Shen (WACV, 2020)

Markov-Lipschitz Deep Learning. - Stan Z. Li; Zelin Zhang; Lirong Wu (CoRR, 2020)

Deep Clustering and Representation Learning that Preserves Geometric Structures. - Lirong Wu; Zicheng Liu 006; Zelin Zang; Jun Xia 001; Siyuan Li 002; Stan Z. Li (CoRR, 2020)

Deep Manifold Computing and Visualization. - Stan Z. Li; Zelin Zang; Lirong Wu (CoRR, 2020)

Consistent Representation Learning for High Dimensional Data Analysis. - Stan Z. Li; Lirong Wu; Zelin Zang (CoRR, 2020)

Co-learning: Learning from Noisy Labels with Self-supervision. - Cheng Tan 012; Jun Xia 001; Lirong Wu; Stan Z. Li (ACM Multimedia, 2021)

Invertible Manifold Learning for Dimension Reduction. - Siyuan Li 002; Haitao Lin; Zelin Zang; Lirong Wu; Jun Xia 001; Stan Z. Li (ECML/PKDD (3), 2021)

Conditional Local Filters with Explainers for Spatio-Temporal Forecasting. - Haitao Lin; Zhangyang Gao; Lirong Wu; Stan Z. Li (CoRR, 2021)

AutoMix: Unveiling the Power of Mixup. - Zicheng Liu 006; Siyuan Li 002; Di Wu 057; Zhiyuan Chen 008; Lirong Wu; Jianzhu Guo; Stan Z. Li (CoRR, 2021)

Self-supervised on Graphs: Contrastive, Generative, or Predictive. - Lirong Wu; Haitao Lin; Zhangyang Gao; Cheng Tan 012; Stan Z. Li (CoRR, 2021)

GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction. - Lirong Wu; Haitao Lin; Zhangyang Gao; Cheng Tan 012; Stan Z. Li (CoRR, 2021)

Git: Clustering Based on Graph of Intensity Topology. - Zhangyang Gao; Haitao Lin; Cheng Tan 012; Lirong Wu; Stan Z. Li (CoRR, 2021)

Debiased Graph Contrastive Learning. - Jun Xia 001; Lirong Wu; Jintao Chen; Ge Wang; Stan Z. Li (CoRR, 2021)

Extensive Deep Temporal Point Process. - Haitao Lin; Cheng Tan 012; Lirong Wu; Zhangyang Gao; Stan Z. Li (CoRR, 2021)

Foreground-Background Parallel Compression With Residual Encoding for Surveillance Video. - Lirong Wu; Kejie Huang; Haibin Shen; Lianli Gao (IEEE Trans. Circuits Syst. Video Technol., 2021)

Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting. - Haitao Lin; Zhangyang Gao; Yongjie Xu; Lirong Wu; Ling Li; Stan Z. Li (AAAI, 2022)

Are Gradients on Graph Structure Reliable in Gray-box Attacks? - Zihan Liu; Yun Luo; Lirong Wu; Siyuan Li 002; Zicheng Liu 006; Stan Z. Li (CIKM, 2022)

Hyperspherical Consistency Regularization. - Cheng Tan 012; Zhangyang Gao; Lirong Wu; Siyuan Li 002; Stan Z. Li (CVPR, 2022)

SimVP: Simpler yet Better Video Prediction. - Zhangyang Gao; Cheng Tan 012; Lirong Wu; Stan Z. Li (CVPR, 2022)

AutoMix: Unveiling the Power of Mixup for Stronger Classifiers. - Zicheng Liu 006; Siyuan Li 002; Di Wu 057; Zihan Liu; Zhiyuan Chen 008; Lirong Wu; Stan Z. Li (ECCV (24), 2022)

OT Cleaner: Label Correction as Optimal Transport. - Jun Xia 001; Cheng Tan 012; Lirong Wu; Yongjie Xu; Stan Z. Li (ICASSP, 2022)

ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning. - Jun Xia 001; Lirong Wu; Ge Wang; Jintao Chen; Stan Z. Li (ICML, 2022)

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias. - Zihan Liu; Yun Luo; Lirong Wu; Zicheng Liu 006; Stan Z. Li (NeurIPS, 2022)

Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks. - Lirong Wu; Haitao Lin; Yufei Huang 002; Stan Z. Li (NeurIPS, 2022)

GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction. - Lirong Wu; Jun Xia 001; Zhangyang Gao; Haitao Lin; Cheng Tan 012; Stan Z. Li (ECML/PKDD (4), 2022)

Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation. - Lirong Wu; Zicheng Liu 006; Jun Xia 001; Zelin Zang; Siyuan Li 002; Stan Z. Li (WACV, 2022)

SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation. - Jun Xia 001; Lirong Wu; Jintao Chen; Bozhen Hu; Stan Z. Li (WWW, 2022)

SemiRetro: Semi-template framework boosts deep retrosynthesis prediction. - Zhangyang Gao; Cheng Tan 012; Lirong Wu; Stan Z. Li (CoRR, 2022)

Decoupled Mixup for Data-efficient Learning. - Zicheng Liu 006; Siyuan Li 002; Ge Wang; Cheng Tan 012; Lirong Wu; Stan Z. Li (CoRR, 2022)

STONet: A Neural-Operator-Driven Spatio-temporal Network. - Haitao Lin; Guojiang Zhao; Lirong Wu; Stan Z. Li (CoRR, 2022)

Discovering the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions. - Fang Wu 002; Siyuan Li 002; Lirong Wu; Dragomir R. Radev; Qiang Zhang 026; Stan Z. Li (CoRR, 2022)

CoSP: Co-supervised pretraining of pocket and ligand. - Zhangyang Gao; Cheng Tan 012; Lirong Wu; Stan Z. Li (CoRR, 2022)

Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification. - Lirong Wu; Jun Xia 001; Haitao Lin; Zhangyang Gao; Zicheng Liu 006; Guojiang Zhao; Stan Z. Li (CoRR, 2022)

Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation. - Lirong Wu; Yufei Huang 002; Haitao Lin; Zicheng Liu 006; Tianyu Fan; Stan Z. Li (CoRR, 2022)

Non-equispaced Fourier Neural Solvers for PDEs. - Haitao Lin; Lirong Wu; Yongjie Xu; Yufei Huang 002; Siyuan Li 002; Guojiang Zhao; Stan Z. Li (CoRR, 2022)

Multi-level disentanglement graph neural network. - Lirong Wu; Haitao Lin; Jun Xia 001; Cheng Tan 012; Stan Z. Li (Neural Comput. Appl., 2022)

Exploring Generative Neural Temporal Point Process. - Haitao Lin; Lirong Wu; Guojiang Zhao; Pai Liu; Stan Z. Li (Trans. Mach. Learn. Res., 2022)

Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework. - Lirong Wu; Haitao Lin; Yufei Huang 002; Tianyu Fan; Stan Z. Li (AAAI, 2023)

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning. - Cheng Tan 012; Zhangyang Gao; Lirong Wu; Yongjie Xu; Jun Xia 001; Siyuan Li 002; Stan Z. Li (CVPR, 2023)

Deep Manifold Graph Auto-Encoder For Attributed Graph Embedding. - Bozhen Hu; Zelin Zang; Jun Xia 001; Lirong Wu; Cheng Tan 012; Stan Z. Li (ICASSP, 2023)

Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs. - Lirong Wu; Haitao Lin; Yufei Huang 002; Stan Z. Li (ICML, 2023)

Harnessing Hard Mixed Samples with Decoupled Regularizer. - Zicheng Liu 006; Siyuan Li 002; Ge Wang; Lirong Wu; Cheng Tan 012; Stan Z. Li (NeurIPS, 2023)

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning. - Cheng Tan 012; Siyuan Li 002; Zhangyang Gao; Wenfei Guan; Zedong Wang; Zicheng Liu 006; Lirong Wu; Stan Z. Li (NeurIPS, 2023)

ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics. - Zhangyang Gao; Cheng Tan 012; Yijie Zhang; Xingran Chen; Lirong Wu; Stan Z. Li (NeurIPS, 2023)

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration. - Haitao Lin; Yufei Huang 002; Odin Zhang; Yunfan Liu 002; Lirong Wu; Siyuan Li 002; Zhiyuan Chen 008; Stan Z. Li (NeurIPS, 2023)

Learning to Augment Graph Structure for both Homophily and Heterophily Graphs. - Lirong Wu; Cheng Tan 012; Zihan Liu; Zhangyang Gao; Haitao Lin; Stan Z. Li (ECML/PKDD (3), 2023)

A Survey on Protein Representation Learning: Retrospect and Prospect. - Lirong Wu; Yufei Huang 002; Haitao Lin; Stan Z. Li (CoRR, 2023)

Explaining Graph Neural Networks via Non-parametric Subgraph Matching. - Fang Wu 002; Siyuan Li 002; Lirong Wu; Dragomir Radev; Yinghui Jiang; Xurui Jin; Zhangming Niu; Stan Z. Li (CoRR, 2023)

Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy. - Yufei Huang 002; Lirong Wu; Haitao Lin; Jiangbin Zheng 002; Ge Wang; Stan Z. Li (CoRR, 2023)

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration. - Haitao Lin; Yufei Huang 002; Haotian Zhang; Lirong Wu; Siyuan Li 002; Zhiyuan Chen 008; Stan Z. Li (CoRR, 2023)

Revisiting the Temporal Modeling in Spatio-Temporal Predictive Learning under A Unified View. - Cheng Tan 012; Jue Wang 004; Zhangyang Gao; Siyuan Li 002; Lirong Wu; Jun Xia 001; Stan Z. Li (CoRR, 2023)

Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction. - Yufei Huang 002; Siyuan Li 002; Jin Su; Lirong Wu; Odin Zhang; Haitao Lin; Jingqi Qi; Zihan Liu; Zhangyang Gao; Yuyang Liu; Jiangbin Zheng 002; Stan Z. Li (CoRR, 2023)

Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive. - Lirong Wu; Haitao Lin; Cheng Tan 012; Zhangyang Gao; Stan Z. Li (IEEE Trans. Knowl. Data Eng., 2023)

Deep Clustering and Visualization for End-to-End High-Dimensional Data Analysis. - Lirong Wu; Lifan Yuan; Guojiang Zhao; Haitao Lin; Stan Z. Li (IEEE Trans. Neural Networks Learn. Syst., 2023)

Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer. - Cheng Tan 012; Zhangyang Gao; Lirong Wu; Jun Xia 001; Jiangbin Zheng 002; Xihong Yang; Yue Liu 008; Bozhen Hu; Stan Z. Li (AAAI, 2024)

Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction. - Yufei Huang 002; Siyuan Li 002; Lirong Wu; Jin Su; Haitao Lin; Odin Zhang; Zihan Liu; Zhangyang Gao; Jiangbin Zheng 002; Stan Z. Li (AAAI, 2024)

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction. - Lirong Wu; Yufei Huang 002; Cheng Tan 012; Zhangyang Gao; Bozhen Hu; Haitao Lin; Zicheng Liu 006; Stan Z. Li (AAAI, 2024)

Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation. - Lirong Wu; Yunfan Liu 002; Haitao Lin; Yufei Huang 002; Stan Z. Li (CIKM, 2024)

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks. - Tianyu Fan; Lirong Wu; Yufei Huang 002; Haitao Lin; Cheng Tan 012; Zhangyang Gao; Stan Z. Li (ICLR, 2024)

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. - Lirong Wu; Yijun Tian 001; Yufei Huang 002; Siyuan Li 002; Haitao Lin; Nitesh V. Chawla; Stan Z. Li (ICLR, 2024)

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge. - Yufei Huang 002; Odin Zhang; Lirong Wu; Cheng Tan 012; Haitao Lin; Zhangyang Gao; Siyuan Li 002; Stan Z. Li (ICML, 2024)

Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective. - Cheng Tan 012; Zhangyang Gao; Hanqun Cao; Xingran Chen; Ge Wang; Lirong Wu; Jun Xia 001; Jiangbin Zheng 002; Stan Z. Li (ICML, 2024)

GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation. - Haitao Lin; Lirong Wu; Yufei Huang 002; Yunfan Liu 002; Odin Zhang; Yuanqing Zhou; Rui Sun; Stan Z. Li (ICML, 2024)

PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching. - Haitao Lin; Odin Zhang; Huifeng Zhao; Dejun Jiang 002; Lirong Wu; Zicheng Liu 006; Yufei Huang 002; Stan Z. Li (ICML, 2024)

Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. - Lirong Wu; Yijun Tian 001; Haitao Lin; Yufei Huang 002; Siyuan Li 002; Nitesh V. Chawla; Stan Z. Li (ICML, 2024)

A Fast BP Imaging Algorithm Based on Coordinate System Grouping. - Shichao Chen; Yabo Liu; Lirong Wu; Ling Wang; Ming Liu (IGARSS, 2024)

UniIF: Unified Molecule Inverse Folding. - Zhangyang Gao; Jue Wang 004; Cheng Tan 012; Lirong Wu; Yufei Huang 002; Siyuan Li 002; Zhirui Ye; Stan Z. Li (NeurIPS, 2024)

Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure. - Bozhen Hu; Cheng Tan 012; Jun Xia 001; Yue Liu 008; Lirong Wu; Jiangbin Zheng 002; Yongjie Xu; Yufei Huang 002; Stan Z. Li (NeurIPS, 2024)

ProtGO: Function-Guided Protein Modeling for Unified Representation Learning. - Bozhen Hu; Cheng Tan 012; Yongjie Xu; Zhangyang Gao; Jun Xia 001; Lirong Wu; Stan Z. Li (NeurIPS, 2024)

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond. - Siyuan Li 002; Luyuan Zhang; Zedong Wang; Di Wu 057; Lirong Wu; Zicheng Liu 006; Jun Xia 001; Cheng Tan 012; Yang Liu 356; Baigui Sun; Stan Z. Li (CoRR, 2024)

Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions. - Rui Sun; Lirong Wu; Haitao Lin; Yufei Huang 002; Stan Z. Li (CoRR, 2024)

Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. - Lirong Wu; Yijun Tian 001; Haitao Lin; Yufei Huang 002; Siyuan Li 002; Nitesh V. Chawla; Stan Z. Li (CoRR, 2024)

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph. - Haitao Lin; Guojiang Zhao; Odin Zhang; Yufei Huang 002; Lirong Wu; Zicheng Liu 006; Siyuan Li 002; Cheng Tan 012; Zhifeng Gao; Stan Z. Li (CoRR, 2024)

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. - Sitao Luan; Chenqing Hua; Qincheng Lu; Liheng Ma; Lirong Wu; Xinyu Wang; Minkai Xu; Xiao-Wen Chang; Doina Precup; Rex Ying; Stan Z. Li; Jian Tang 005; et al. (CoRR, 2024)

FM-TS: Flow Matching for Time Series Generation. - Yang Hu; Xiao Wang 012; Lirong Wu; Huatian Zhang 001; Stan Z. Li; Sheng Wang 012; Tianlong Chen 001 (CoRR, 2024)

GNN Cleaner: Label Cleaner for Graph Structured Data. - Jun Xia 001; Haitao Lin; Yongjie Xu; Cheng Tan 012; Lirong Wu; Siyuan Li 002; Stan Z. Li (IEEE Trans. Knowl. Data Eng., 2024)

Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks. - Lirong Wu; Haitao Lin; Bozhen Hu; Cheng Tan 012; Zhangyang Gao; Zicheng Liu 006; Stan Z. Li (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Teacher-Free Graph Knowledge Distillation Framework With Dual Self-Distillation. - Lirong Wu; Haitao Lin; Zhangyang Gao; Guojiang Zhao; Stan Z. Li (IEEE Trans. Knowl. Data Eng., 2024)

Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions. - Lirong Wu; Haitao Lin; Zihan Liu; Zicheng Liu 006; Yufei Huang 002; Stan Z. Li (IEEE Trans. Neural Networks Learn. Syst., 2024)

dyAb: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigen. - Cheng Tan 012; Yijie Zhang; Zhangyang Gao; Yufei Huang 002; Haitao Lin; Lirong Wu; Fandi Wu; Mathieu Blanchette; Stan Z. Li (AAAI, 2025)

FoldToken: Learning Protein Language via Vector Quantization and Beyond. - Zhangyang Gao; Cheng Tan 012; Jue Wang 004; Yufei Huang 002; Lirong Wu; Stan Z. Li (AAAI, 2025)

Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization. - Lirong Wu; Haitao Lin; Yufei Huang 002; Zhangyang Gao; Cheng Tan 012; Yunfan Liu 002; Tailin Wu; Stan Z. Li (AAAI, 2025)

DaCapo: Score Distillation as Stacked Bridge for Fast and High-quality 3D Editing. - Yufei Huang 002; Bangyan Liao; Yuqi Hu; Haitao Lin; Lirong Wu; Siyuan Li 002; Cheng Tan 012; Zicheng Liu 006; Yunfan Liu 002; Zelin Zang; Chang Yu 001; Zhen Lei 001 (CVPR, 2025)

EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow. - Yufei Huang 002; Yunshu Liu; Lirong Wu; Haitao Lin; Cheng Tan 012; Odin Zhang; Zhangyang Gao; Siyuan Li 002; Zicheng Liu 006; Yunfan Liu 002; Tailin Wu; Stan Z. Li (ICLR, 2025)

MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction. - Cheng Tan 012; Zhenxiao Cao; Zhangyang Gao; Lirong Wu; Siyuan Li 002; Yufei Huang 002; Jun Xia 001; Bozhen Hu; Stan Z. Li (ICLR, 2025)

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph. - Haitao Lin; Guojiang Zhao; Odin Zhang; Yufei Huang 002; Lirong Wu; Cheng Tan 012; Zicheng Liu 006; Zhifeng Gao; Stan Z. Li (ICLR, 2025)

A Simple yet Effective ΔΔG Predictor is An Unsupervised Antibody Optimizer and Explainer. - Lirong Wu; Yunfan Liu 002; Haitao Lin; Yufei Huang 002; Guojiang Zhao; Zhifeng Gao; Stan Z. Li (ICLR, 2025)

Data-Driven Parametrization of All-Atom Force Fields for Organic Semiconductors. - Guojiang Zhao; Taiping Hu; Yingfeng Zhang; Hongshuai Wang; Lirong Wu; Shuqi Lu; Fengtianci Yang; Shangqian Chen; Zhifeng Gao; Xinyan Wang; Zheng Cheng (J. Chem. Inf. Model., 2025)

A Simple yet Effective DDG Predictor is An Unsupervised Antibody Optimizer and Explainer. - Lirong Wu; Yunfan Liu 002; Haitao Lin; Yufei Huang 002; Guojiang Zhao; Zhifeng Gao; Stan Z. Li (CoRR, 2025)

An Extensive Survey With Empirical Studies on Deep Temporal Point Process. - Haitao Lin; Cheng Tan 012; Lirong Wu; Zicheng Liu 006; Zhangyang Gao; Stan Z. Li (IEEE Trans. Knowl. Data Eng., 2025)

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning. - Haitao Lin; Odin Zhang; Jia Xu; Yunfan Liu 002; Zheng Chen 014; Lirong Wu; Yufei Huang 002; Zhifeng Gao; Stan Z. Li (CoRR, 2025)

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting. - Lirong Wu; Haitao Lin; Guojiang Zhao; Cheng Tan 012; Stan Z. Li (IEEE Trans. Neural Networks Learn. Syst., 2025)

MolReasoner: Toward Effective and Interpretable Reasoning for Molecular LLMs. - Guojiang Zhao; Sihang Li 002; Zixiang Lu; Zheng Cheng; Haitao Lin; Lirong Wu; Hanchen Xia; Hengxing Cai; Wentao Guo; Hongshuai Wang; Mingjun Xu; Siyu Zhu; et al. (CoRR, 2025)