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2020 – today
- 2024
- [j9]Jun Xia, Haitao Lin, Yongjie Xu, Cheng Tan, Lirong Wu, Siyuan Li, Stan Z. Li:
GNN Cleaner: Label Cleaner for Graph Structured Data. IEEE Trans. Knowl. Data Eng. 36(2): 640-651 (2024) - [j8]Lirong Wu, Haitao Lin, Zhangyang Gao, Guojiang Zhao, Stan Z. Li:
A Teacher-Free Graph Knowledge Distillation Framework With Dual Self-Distillation. IEEE Trans. Knowl. Data Eng. 36(9): 4375-4385 (2024) - [j7]Lirong Wu, Haitao Lin, Bozhen Hu, Cheng Tan, Zhangyang Gao, Zicheng Liu, Stan Z. Li:
Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(6): 8497-8509 (2024) - [j6]Lirong Wu, Haitao Lin, Zihan Liu, Zicheng Liu, Yufei Huang, Stan Z. Li:
Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12358-12372 (2024) - [c38]Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li:
PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction. AAAI 2024: 310-319 - [c37]Yufei Huang, Siyuan Li, Lirong Wu, Jin Su, Haitao Lin, Odin Zhang, Zihan Liu, Zhangyang Gao, Jiangbin Zheng, Stan Z. Li:
Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction. AAAI 2024: 12662-12670 - [c36]Cheng Tan, Zhangyang Gao, Lirong Wu, Jun Xia, Jiangbin Zheng, Xihong Yang, Yue Liu, Bozhen Hu, Stan Z. Li:
Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer. AAAI 2024: 15222-15230 - [c35]Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Stan Z. Li:
Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation. CIKM 2024: 2554-2563 - [c34]Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li:
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks. ICLR 2024 - [c33]Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li:
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. ICLR 2024 - [c32]Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin, Zhangyang Gao, Siyuan Li, Stan Z. Li:
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge. ICML 2024 - [c31]Cheng Tan, Zhangyang Gao, Hanqun Cao, Xingran Chen, Ge Wang, Lirong Wu, Jun Xia, Jiangbin Zheng, Stan Z. Li:
Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective. ICML 2024 - [c30]Haitao Lin, Lirong Wu, Yufei Huang, Yunfan Liu, Odin Zhang, Yuanqing Zhou, Rui Sun, Stan Z. Li:
GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation. ICML 2024 - [c29]Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li:
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching. ICML 2024 - [c28]Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li:
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. ICML 2024 - [c27]Shichao Chen, Yabo Liu, Lirong Wu, Ling Wang, Ming Liu:
A Fast BP Imaging Algorithm Based on Coordinate System Grouping. IGARSS 2024: 11388-11391 - [i54]Siyuan Li, Luyuan Zhang, Zedong Wang, Di Wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li:
Masked Modeling for Self-supervised Representation Learning on Vision and Beyond. CoRR abs/2401.00897 (2024) - [i53]Bozhen Hu, Zelin Zang, Jun Xia, Lirong Wu, Cheng Tan, Stan Z. Li:
Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding. CoRR abs/2401.06727 (2024) - [i52]Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li:
PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction. CoRR abs/2402.08198 (2024) - [i51]Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin, Zhangyang Gao, Siyuan Li, Stan Z. Li:
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge. CoRR abs/2402.11459 (2024) - [i50]Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li:
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. CoRR abs/2402.14391 (2024) - [i49]Rui Sun, Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li:
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions. CoRR abs/2403.00875 (2024) - [i48]Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li:
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks. CoRR abs/2403.01400 (2024) - [i47]Lirong Wu, Haitao Lin, Zhangyang Gao, Guojiang Zhao, Stan Z. Li:
A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation. CoRR abs/2403.03483 (2024) - [i46]Zhangyang Gao, Cheng Tan, Jue Wang, Yufei Huang, Lirong Wu, Stan Z. Li:
FoldToken: Learning Protein Language via Vector Quantization and Beyond. CoRR abs/2403.09673 (2024) - [i45]Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li:
PPFlow: Target-aware Peptide Design with Torsional Flow Matching. CoRR abs/2405.06642 (2024) - [i44]Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li:
Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. CoRR abs/2405.10348 (2024) - [i43]Zhangyang Gao, Jue Wang, Cheng Tan, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li:
UniIF: Unified Molecule Inverse Folding. CoRR abs/2405.18968 (2024) - [i42]Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Zicheng Liu, Siyuan Li, Cheng Tan, Zhifeng Gao, Stan Z. Li:
CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph. CoRR abs/2406.10840 (2024) - [i41]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:
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. CoRR abs/2407.09618 (2024) - [i40]Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Stan Z. Li:
Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation. CoRR abs/2407.14768 (2024) - [i39]Lirong Wu, Haitao Lin, Guojiang Zhao, Cheng Tan, Stan Z. Li:
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting. CoRR abs/2409.05573 (2024) - 2023
- [j5]Lirong Wu, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li:
Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive. IEEE Trans. Knowl. Data Eng. 35(4): 4216-4235 (2023) - [j4]Lirong Wu, Lifan Yuan, Guojiang Zhao, Haitao Lin, Stan Z. Li:
Deep Clustering and Visualization for End-to-End High-Dimensional Data Analysis. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8543-8554 (2023) - [c26]Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li:
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework. AAAI 2023: 10351-10360 - [c25]Cheng Tan, Zhangyang Gao, Lirong Wu, Yongjie Xu, Jun Xia, Siyuan Li, Stan Z. Li:
Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning. CVPR 2023: 18770-18782 - [c24]Bozhen Hu, Zelin Zang, Jun Xia, Lirong Wu, Cheng Tan, Stan Z. Li:
Deep Manifold Graph Auto-Encoder For Attributed Graph Embedding. ICASSP 2023: 1-5 - [c23]Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li:
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs. ICML 2023: 37571-37581 - [c22]Zicheng Liu, Siyuan Li, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li:
Harnessing Hard Mixed Samples with Decoupled Regularizer. NeurIPS 2023 - [c21]Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li:
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning. NeurIPS 2023 - [c20]Zhangyang Gao, Cheng Tan, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li:
ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics. NeurIPS 2023 - [c19]Haitao Lin, Yufei Huang, Odin Zhang, Yunfan Liu, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li:
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration. NeurIPS 2023 - [c18]Lirong Wu, Cheng Tan, Zihan Liu, Zhangyang Gao, Haitao Lin, Stan Z. Li:
Learning to Augment Graph Structure for both Homophily and Heterophily Graphs. ECML/PKDD (3) 2023: 3-18 - [i38]Lirong Wu, Yufei Huang, Haitao Lin, Stan Z. Li:
A Survey on Protein Representation Learning: Retrospect and Prospect. CoRR abs/2301.00813 (2023) - [i37]Fang Wu, Siyuan Li, Lirong Wu, Dragomir Radev, Yinghui Jiang, Xurui Jin, Zhangming Niu, Stan Z. Li:
Explaining Graph Neural Networks via Non-parametric Subgraph Matching. CoRR abs/2301.02780 (2023) - [i36]Yufei Huang, Lirong Wu, Haitao Lin, Jiangbin Zheng, Ge Wang, Stan Z. Li:
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy. CoRR abs/2302.10888 (2023) - [i35]Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li:
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias. CoRR abs/2304.00010 (2023) - [i34]Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li:
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework. CoRR abs/2305.10758 (2023) - [i33]Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li:
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs. CoRR abs/2306.05628 (2023) - [i32]Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li:
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning. CoRR abs/2306.11249 (2023) - [i31]Haitao Lin, Yufei Huang, Haotian Zhang, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li:
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration. CoRR abs/2306.13769 (2023) - [i30]Cheng Tan, Jue Wang, Zhangyang Gao, Siyuan Li, Lirong Wu, Jun Xia, Stan Z. Li:
Revisiting the Temporal Modeling in Spatio-Temporal Predictive Learning under A Unified View. CoRR abs/2310.05829 (2023) - [i29]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:
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction. CoRR abs/2310.11466 (2023) - 2022
- [j3]Lirong Wu, Haitao Lin, Jun Xia, Cheng Tan, Stan Z. Li:
Multi-level disentanglement graph neural network. Neural Comput. Appl. 34(11): 9087-9101 (2022) - [j2]Haitao Lin, Lirong Wu, Guojiang Zhao, Pai Liu, Stan Z. Li:
Exploring Generative Neural Temporal Point Process. Trans. Mach. Learn. Res. 2022 (2022) - [c17]Haitao Lin, Zhangyang Gao, Yongjie Xu, Lirong Wu, Ling Li, Stan Z. Li:
Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting. AAAI 2022: 7470-7478 - [c16]Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li:
Are Gradients on Graph Structure Reliable in Gray-box Attacks? CIKM 2022: 1360-1368 - [c15]Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li:
SimVP: Simpler yet Better Video Prediction. CVPR 2022: 3160-3170 - [c14]Cheng Tan, Zhangyang Gao, Lirong Wu, Siyuan Li, Stan Z. Li:
Hyperspherical Consistency Regularization. CVPR 2022: 7234-7245 - [c13]Zicheng Liu, Siyuan Li, Di Wu, Zihan Liu, Zhiyuan Chen, Lirong Wu, Stan Z. Li:
AutoMix: Unveiling the Power of Mixup for Stronger Classifiers. ECCV (24) 2022: 441-458 - [c12]Jun Xia, Cheng Tan, Lirong Wu, Yongjie Xu, Stan Z. Li:
OT Cleaner: Label Correction as Optimal Transport. ICASSP 2022: 3953-3957 - [c11]Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li:
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning. ICML 2022: 24332-24346 - [c10]Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li:
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias. NeurIPS 2022 - [c9]Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li:
Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks. NeurIPS 2022 - [c8]Lirong Wu, Jun Xia, Zhangyang Gao, Haitao Lin, Cheng Tan, Stan Z. Li:
GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction. ECML/PKDD (4) 2022: 519-535 - [c7]Lirong Wu, Zicheng Liu, Jun Xia, Zelin Zang, Siyuan Li, Stan Z. Li:
Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation. WACV 2022: 1668-1676 - [c6]Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li:
SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation. WWW 2022: 1070-1079 - [i28]Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li:
SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation. CoRR abs/2202.03104 (2022) - [i27]Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li:
SemiRetro: Semi-template framework boosts deep retrosynthesis prediction. CoRR abs/2202.08205 (2022) - [i26]Zicheng Liu, Siyuan Li, Ge Wang, Cheng Tan, Lirong Wu, Stan Z. Li:
Decoupled Mixup for Data-efficient Learning. CoRR abs/2203.10761 (2022) - [i25]Haitao Lin, Guojiang Zhao, Lirong Wu, Stan Z. Li:
STONet: A Neural-Operator-Driven Spatio-temporal Network. CoRR abs/2204.08414 (2022) - [i24]Fang Wu, Siyuan Li, Lirong Wu, Dragomir R. Radev, Qiang Zhang, Stan Z. Li:
Discovering the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions. CoRR abs/2205.07266 (2022) - [i23]Cheng Tan, Zhangyang Gao, Lirong Wu, Siyuan Li, Stan Z. Li:
Hyperspherical Consistency Regularization. CoRR abs/2206.00845 (2022) - [i22]Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li:
SimVP: Simpler yet Better Video Prediction. CoRR abs/2206.05099 (2022) - [i21]Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li:
CoSP: Co-supervised pretraining of pocket and ligand. CoRR abs/2206.12241 (2022) - [i20]Haitao Lin, Lirong Wu, Guojiang Zhao, Pai Liu, Stan Z. Li:
Exploring Generative Neural Temporal Point Process. CoRR abs/2208.01874 (2022) - [i19]Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li:
Are Gradients on Graph Structure Reliable in Gray-box Attacks? CoRR abs/2208.05514 (2022) - [i18]Lirong Wu, Jun Xia, Haitao Lin, Zhangyang Gao, Zicheng Liu, Guojiang Zhao, Stan Z. Li:
Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification. CoRR abs/2210.02097 (2022) - [i17]Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li:
Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation. CoRR abs/2210.02099 (2022) - [i16]Haitao Lin, Lirong Wu, Yongjie Xu, Yufei Huang, Siyuan Li, Guojiang Zhao, Stan Z. Li:
Non-equispaced Fourier Neural Solvers for PDEs. CoRR abs/2212.04689 (2022) - 2021
- [j1]Lirong Wu, Kejie Huang, Haibin Shen, Lianli Gao:
Foreground-Background Parallel Compression With Residual Encoding for Surveillance Video. IEEE Trans. Circuits Syst. Video Technol. 31(7): 2711-2724 (2021) - [c5]Cheng Tan, Jun Xia, Lirong Wu, Stan Z. Li:
Co-learning: Learning from Noisy Labels with Self-supervision. ACM Multimedia 2021: 1405-1413 - [c4]Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li:
Invertible Manifold Learning for Dimension Reduction. ECML/PKDD (3) 2021: 713-728 - [i15]Haitao Lin, Zhangyang Gao, Lirong Wu, Stan Z. Li:
Conditional Local Filters with Explainers for Spatio-Temporal Forecasting. CoRR abs/2101.01000 (2021) - [i14]Zicheng Liu, Siyuan Li, Di Wu, Zhiyuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li:
AutoMix: Unveiling the Power of Mixup. CoRR abs/2103.13027 (2021) - [i13]Lirong Wu, Haitao Lin, Zhangyang Gao, Cheng Tan, Stan Z. Li:
Self-supervised on Graphs: Contrastive, Generative, or Predictive. CoRR abs/2105.07342 (2021) - [i12]Lirong Wu, Haitao Lin, Zhangyang Gao, Cheng Tan, Stan Z. Li:
GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction. CoRR abs/2106.11133 (2021) - [i11]Cheng Tan, Jun Xia, Lirong Wu, Stan Z. Li:
Co-learning: Learning from Noisy Labels with Self-supervision. CoRR abs/2108.04063 (2021) - [i10]Zhangyang Gao, Haitao Lin, Cheng Tan, Lirong Wu, Stan Z. Li:
Git: Clustering Based on Graph of Intensity Topology. CoRR abs/2110.01274 (2021) - [i9]Jun Xia, Lirong Wu, Jintao Chen, Ge Wang, Stan Z. Li:
Debiased Graph Contrastive Learning. CoRR abs/2110.02027 (2021) - [i8]Haitao Lin, Cheng Tan, Lirong Wu, Zhangyang Gao, Stan Z. Li:
Extensive Deep Temporal Point Process. CoRR abs/2110.09823 (2021) - 2020
- [c3]Lirong Wu, Kejie Huang, Haibin Shen:
A GAN-based Tunable Image Compression System. WACV 2020: 2323-2331 - [i7]Lirong Wu, Kejie Huang, Haibin Shen:
A GAN-based Tunable Image Compression System. CoRR abs/2001.06580 (2020) - [i6]Lirong Wu, Kejie Huang, Haibin Shen, Lianli Gao:
A Foreground-background Parallel Compression with Residual Encoding for Surveillance Video. CoRR abs/2001.06590 (2020) - [i5]Stan Z. Li, Zelin Zhang, Lirong Wu:
Markov-Lipschitz Deep Learning. CoRR abs/2006.08256 (2020) - [i4]Lirong Wu, Zicheng Liu, Zelin Zang, Jun Xia, Siyuan Li, Stan Z. Li:
Deep Clustering and Representation Learning that Preserves Geometric Structures. CoRR abs/2009.09590 (2020) - [i3]Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li:
Invertible Manifold Learning for Dimension Reduction. CoRR abs/2010.04012 (2020) - [i2]Stan Z. Li, Zelin Zang, Lirong Wu:
Deep Manifold Computing and Visualization. CoRR abs/2010.14831 (2020) - [i1]Stan Z. Li, Lirong Wu, Zelin Zang:
Consistent Representation Learning for High Dimensional Data Analysis. CoRR abs/2012.00481 (2020)
2010 – 2019
- 2011
- [c2]Xiangpei Hu, Lirong Wu, Chao Li, Minfang Huang:
SMS-based Mobile Recommendation System for Campus Recruitment in China. ICMB 2011: 152-157
2000 – 2009
- 2006
- [c1]Xun-Kai Wei, Chong Duan, Ying Hong Li, Lirong Wu:
Ramp Shape Optimum Design for Airplane Land-Based Ski-Jump Takeoff via NSGA II. ISDA (2) 2006: 995-1000
Coauthor Index
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