Lirong Wu

According to our database, Lirong Wu authored at least 79 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions.

Lirong Wu, Haitao Lin, Zihan Liu, Zicheng Liu, Yufei Huang, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., September, 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., September, 2024

Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks.

Lirong Wu, Haitao Lin, Bozhen Hu, Cheng Tan, Zhangyang Gao, Zicheng Liu, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., June, 2024

GNN Cleaner: Label Cleaner for Graph Structured Data.

Jun Xia, Haitao Lin, Yongjie Xu, Cheng Tan, Lirong Wu, Siyuan Li, Stan Z. Li

IEEE Trans. Knowl. Data Eng., February, 2024

Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation.

Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, 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, Guy Wolf, Stefanie Jegelka

CoRR, 2024

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.

Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Zicheng Liu, Siyuan Li, Cheng Tan, Zhifeng Gao, Stan Z. Li

CoRR, 2024

UniIF: Unified Molecule Inverse Folding.

Zhangyang Gao, Jue Wang, Cheng Tan, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li

CoRR, 2024

Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li

CoRR, 2024

FoldToken: Learning Protein Language via Vector Quantization and Beyond.

Zhangyang Gao, Cheng Tan, Jue Wang, Yufei Huang, Lirong Wu, 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, Stan Z. Li

CoRR, 2024

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond.

Siyuan Li, Luyuan Zhang, Zedong Wang, Di Wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

A Fast BP Imaging Algorithm Based on Coordinate System Grouping.

Shichao Chen, Yabo Liu, Lirong Wu, Ling Wang, Ming Liu

Proceedings of the IGARSS 2024, 2024

Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching.

Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation.

Haitao Lin, Lirong Wu, Yufei Huang, Yunfan Liu, Odin Zhang, Yuanqing Zhou, Rui Sun, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective.

Cheng Tan, Zhangyang Gao, Hanqun Cao, Xingran Chen, Ge Wang, Lirong Wu, Jun Xia, Jiangbin Zheng, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge.

Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin, Zhangyang Gao, Siyuan Li, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding.

Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks.

Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction.

Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction.

Yufei Huang, Siyuan Li, Lirong Wu, Jin Su, Haitao Lin, Odin Zhang, Zihan Liu, Zhangyang Gao, Jiangbin Zheng, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer.

Cheng Tan, Zhangyang Gao, Lirong Wu, Jun Xia, Jiangbin Zheng, Xihong Yang, Yue Liu, Bozhen Hu, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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., November, 2023

Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive.

Lirong Wu, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

IEEE Trans. Knowl. Data Eng., April, 2023

Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction.

Yufei Huang, Siyuan Li, Jin Su, Lirong Wu, Odin Zhang, Haitao Lin, Jingqi Qi, Zihan Liu, Zhangyang Gao, Yuyang Liu, Jiangbin Zheng, Stan Z. Li

CoRR, 2023

Revisiting the Temporal Modeling in Spatio-Temporal Predictive Learning under A Unified View.

Cheng Tan, Jue Wang, Zhangyang Gao, Siyuan Li, Lirong Wu, Jun Xia, Stan Z. Li

CoRR, 2023

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration.

Haitao Lin, Yufei Huang, Haotian Zhang, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li

CoRR, 2023

Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy.

Yufei Huang, Lirong Wu, Haitao Lin, Jiangbin Zheng, Ge Wang, Stan Z. Li

CoRR, 2023

Explaining Graph Neural Networks via Non-parametric Subgraph Matching.

Fang Wu, Siyuan Li, Lirong Wu, Dragomir Radev, Yinghui Jiang, Xurui Jin, Zhangming Niu, Stan Z. Li

CoRR, 2023

A Survey on Protein Representation Learning: Retrospect and Prospect.

Lirong Wu, Yufei Huang, Haitao Lin, Stan Z. Li

CoRR, 2023

Learning to Augment Graph Structure for both Homophily and Heterophily Graphs.

Lirong Wu, Cheng Tan, Zihan Liu, Zhangyang Gao, Haitao Lin, Stan Z. Li

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration.

Haitao Lin, Yufei Huang, Odin Zhang, Yunfan Liu, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics.

Zhangyang Gao, Cheng Tan, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning.

Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Harnessing Hard Mixed Samples with Decoupled Regularizer.

Zicheng Liu, Siyuan Li, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs.

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 2023

Deep Manifold Graph Auto-Encoder For Attributed Graph Embedding.

Bozhen Hu, Zelin Zang, Jun Xia, Lirong Wu, Cheng Tan, Stan Z. Li

Proceedings of the IEEE International Conference on Acoustics, 2023

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning.

Cheng Tan, Zhangyang Gao, Lirong Wu, Yongjie Xu, Jun Xia, Siyuan Li, Stan Z. Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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, Tianyu Fan, Stan Z. Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Exploring Generative Neural Temporal Point Process.

Haitao Lin, Lirong Wu, Guojiang Zhao, Pai Liu, Stan Z. Li

Trans. Mach. Learn. Res., 2022

Multi-level disentanglement graph neural network.

Lirong Wu, Haitao Lin, Jun Xia, Cheng Tan, Stan Z. Li

Neural Comput. Appl., 2022

Non-equispaced Fourier Neural Solvers for PDEs.

Haitao Lin, Lirong Wu, Yongjie Xu, Yufei Huang, Siyuan Li, Guojiang Zhao, Stan Z. Li

CoRR, 2022

Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation.

Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li

CoRR, 2022

Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification.

Lirong Wu, Jun Xia, Haitao Lin, Zhangyang Gao, Zicheng Liu, Guojiang Zhao, Stan Z. Li

CoRR, 2022

CoSP: Co-supervised pretraining of pocket and ligand.

Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li

CoRR, 2022

Discovering the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions.

Fang Wu, Siyuan Li, Lirong Wu, Dragomir R. Radev, Qiang Zhang, Stan Z. Li

CoRR, 2022

STONet: A Neural-Operator-Driven Spatio-temporal Network.

Haitao Lin, Guojiang Zhao, Lirong Wu, Stan Z. Li

CoRR, 2022

Decoupled Mixup for Data-efficient Learning.

Zicheng Liu, Siyuan Li, Ge Wang, Cheng Tan, Lirong Wu, Stan Z. Li

CoRR, 2022

SemiRetro: Semi-template framework boosts deep retrosynthesis prediction.

Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li

CoRR, 2022

SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation.

Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation.

Lirong Wu, Zicheng Liu, Jun Xia, Zelin Zang, Siyuan Li, Stan Z. Li

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction.

Lirong Wu, Jun Xia, Zhangyang Gao, Haitao Lin, Cheng Tan, Stan Z. Li

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.

Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning.

Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 2022

OT Cleaner: Label Correction as Optimal Transport.

Jun Xia, Cheng Tan, Lirong Wu, Yongjie Xu, Stan Z. Li

Proceedings of the IEEE International Conference on Acoustics, 2022

AutoMix: Unveiling the Power of Mixup for Stronger Classifiers.

Zicheng Liu, Siyuan Li, Di Wu, Zihan Liu, Zhiyuan Chen, Lirong Wu, Stan Z. Li

Proceedings of the Computer Vision, 2022

SimVP: Simpler yet Better Video Prediction.

Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Hyperspherical Consistency Regularization.

Cheng Tan, Zhangyang Gao, Lirong Wu, Siyuan Li, Stan Z. Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Are Gradients on Graph Structure Reliable in Gray-box Attacks?

Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting.

Haitao Lin, Zhangyang Gao, Yongjie Xu, Lirong Wu, Ling Li, Stan Z. Li

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

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

Extensive Deep Temporal Point Process.

Haitao Lin, Cheng Tan, Lirong Wu, Zhangyang Gao, Stan Z. Li

CoRR, 2021

Debiased Graph Contrastive Learning.

Jun Xia, Lirong Wu, Jintao Chen, Ge Wang, Stan Z. Li

CoRR, 2021

Git: Clustering Based on Graph of Intensity Topology.

Zhangyang Gao, Haitao Lin, Cheng Tan, Lirong Wu, 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, Stan Z. Li

CoRR, 2021

Self-supervised on Graphs: Contrastive, Generative, or Predictive.

Lirong Wu, Haitao Lin, Zhangyang Gao, Cheng Tan, Stan Z. Li

CoRR, 2021

AutoMix: Unveiling the Power of Mixup.

Zicheng Liu, Siyuan Li, Di Wu, Zhiyuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li

CoRR, 2021

Conditional Local Filters with Explainers for Spatio-Temporal Forecasting.

Haitao Lin, Zhangyang Gao, Lirong Wu, Stan Z. Li

CoRR, 2021

Invertible Manifold Learning for Dimension Reduction.

Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Co-learning: Learning from Noisy Labels with Self-supervision.

Cheng Tan, Jun Xia, Lirong Wu, Stan Z. Li

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020

Consistent Representation Learning for High Dimensional Data Analysis.

Stan Z. Li, Lirong Wu, Zelin Zang

CoRR, 2020

Deep Manifold Computing and Visualization.

Stan Z. Li, Zelin Zang, Lirong Wu

CoRR, 2020

Deep Clustering and Representation Learning that Preserves Geometric Structures.

Lirong Wu, Zicheng Liu, Zelin Zang, Jun Xia, Siyuan Li, Stan Z. Li

CoRR, 2020

Markov-Lipschitz Deep Learning.

Stan Z. Li, Zelin Zhang, Lirong Wu

CoRR, 2020

A GAN-based Tunable Image Compression System.

Lirong Wu, Kejie Huang, Haibin Shen

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

2011

SMS-based Mobile Recommendation System for Campus Recruitment in China.

Xiangpei Hu, Lirong Wu, Chao Li, Minfang Huang

Proceedings of the International Conference on Mobile Business (ICMB 2011), 2011

2006

Ramp Shape Optimum Design for Airplane Land-Based Ski-Jump Takeoff via NSGA II.

Xun-Kai Wei, Chong Duan, Ying Hong Li, Lirong Wu

Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA 2006), 2006