Cheng Tan

According to our database, Cheng Tan authored at least 68 papers between 2020 and 2024.

Collaborative distances:

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

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

FoldToken: Learning Protein Language via Vector Quantization and Beyond.

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

CoRR, 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

CoRR, 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

CoRR, 2024

Deep Manifold Transformation for Protein Representation Learning.

Bozhen Hu, Zelin Zang, Cheng Tan, Stan Z. Li

CoRR, 2024

Switch EMA: A Free Lunch for Better Flatness and Sharpness.

Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di Wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer.

Zhangyang Gao, Daize Dong, Cheng Tan, Jun Xia, Bozhen Hu, Stan Z. Li

CoRR, 2024

DCS-Net: Pioneering Leakage-Free Point Cloud Pretraining Framework with Global Insights.

Zhe Li, Zhangyang Gao, Cheng Tan, Stan Z. Li, Laurence T. Yang

CoRR, 2024

MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning.

Zhe Li, Laurence T. Yang, Bocheng Ren, Xin Nie, Zhangyang Gao, Cheng Tan, 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

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

Wavelet-Driven Spatiotemporal Predictive Learning: Bridging Frequency and Time Variations.

Xuesong Nie, Yunfeng Yan, Siyuan Li, Cheng Tan, Xi Chen, Haoyuan Jin, Zhihang Zhu, Stan Z. Li, Donglian Qi

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

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

MMDesign: Multi-Modality Transfer Learning for Generative Protein Design.

Jiangbin Zheng, Siyuan Li, Yufei Huang, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jun Xia, Ge Wang, Stan Z. Li

CoRR, 2023

Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Models.

Yijie Zhang, Zhangyang Gao, Cheng Tan, Stan Z. Li

CoRR, 2023

Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training.

Cheng Tan, Jingxuan Wei, Zhangyang Gao, Linzhuang Sun, Siyuan Li, Xihong Yang, Stan Z. Li

CoRR, 2023

Segment Anything in Defect Detection.

Bozhen Hu, Bin Gao, Cheng Tan, Tongle Wu, Stan Z. Li

CoRR, 2023

General Point Model with Autoencoding and Autoregressive.

Zhe Li, Zhangyang Gao, Cheng Tan, Stan Z. Li, Laurence T. Yang

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

VQPL: Vector Quantized Protein Language.

Zhangyang Gao, Cheng Tan, Stan Z. Li

CoRR, 2023

SemiReward: A General Reward Model for Semi-supervised Learning.

Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li

CoRR, 2023

Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework.

Jingxuan Wei, Cheng Tan, Zhangyang Gao, Linzhuang Sun, Siyuan Li, Bihui Yu, Ruifeng Guo, Stan Z. Li

CoRR, 2023

MotifRetro: Exploring the Combinability-Consistency Trade-offs in retrosynthesis via Dynamic Motif Editing.

Zhangyang Gao, Xingran Chen, Cheng Tan, Stan Z. Li

CoRR, 2023

Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement.

Zhangyang Gao, Cheng Tan, Stan Z. Li

CoRR, 2023

Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designer.

Cheng Tan, Zhangyang Gao, Stan Z. Li

CoRR, 2023

Lightweight Contrastive Protein Structure-Sequence Transformation.

Jiangbin Zheng, Ge Wang, Yufei Huang, Bozhen Hu, Siyuan Li, Cheng Tan, Xinwen Fan, Stan Z. Li

CoRR, 2023

PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embedding.

Zhangyang Gao, Yuqi Hu, Cheng Tan, Stan Z. Li

CoRR, 2023

Generative Tertiary Structure-based RNA Design.

Cheng Tan, Zhangyang Gao, Stan Z. Li

CoRR, 2023

DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraints.

Zhangyang Gao, Cheng Tan, 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

Target-Aware Molecular Graph Generation.

Cheng Tan, Zhangyang Gao, Stan Z. Li

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Co-supervised Pre-training of Pocket and Ligand.

Zhangyang Gao, Cheng Tan, Jun Xia, Stan Z. Li

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

Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions.

Jun Xia, Lecheng Zhang, Xiao Zhu, Yue Liu, Zhangyang Gao, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Siyuan Li, 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

CONVERT: Contrastive Graph Clustering with Reliable Augmentation.

Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules.

Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

PiFold: Toward effective and efficient protein inverse folding.

Zhangyang Gao, Cheng Tan, Stan Z. Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Wordreg: Mitigating the Gap between Training and Inference with Worst-Case Drop Regularization.

Jun Xia, Ge Wang, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Yongjie Xu, Stan Z. Li

Proceedings of the IEEE International Conference on Acoustics, 2023

Global-Context Aware Generative Protein Design.

Cheng Tan, Zhangyang Gao, Jun Xia, Bozhen Hu, Stan Z. Li

Proceedings of the IEEE International Conference on Acoustics, 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

CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment.

Jiangbin Zheng, Yile Wang, Cheng Tan, Siyuan Li, Ge Wang, Jun Xia, Yidong Chen, Stan Z. Li

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

2022

Multi-level disentanglement graph neural network.

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

Neural Comput. Appl., 2022

RFold: Towards Simple yet Effective RNA Secondary Structure Prediction.

Cheng Tan, Zhangyang Gao, Stan Z. Li

CoRR, 2022

Protein Language Models and Structure Prediction: Connection and Progression.

Bozhen Hu, Jun Xia, Jiangbin Zheng, Cheng Tan, Yufei Huang, Yongjie Xu, Stan Z. Li

CoRR, 2022

SimVP: Towards Simple yet Powerful Spatiotemporal Predictive Learning.

Cheng Tan, Zhangyang Gao, Stan Z. Li

CoRR, 2022

Efficient Multi-order Gated Aggregation Network.

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

CoRR, 2022

Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation.

Jiangbin Zheng, Siyuan Li, Cheng Tan, Chong Wu, Yidong Chen, Stan Z. Li

CoRR, 2022

A Survey on Generative Diffusion Model.

Hanqun Cao, Cheng Tan, Zhangyang Gao, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li

CoRR, 2022

CoSP: Co-supervised pretraining of pocket and ligand.

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

CoRR, 2022

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning.

Cheng Tan, Zhangyang Gao, Siyuan Li, Yongjie Xu, Stan Z. Li

CoRR, 2022

Generative De Novo Protein Design with Global Context.

Cheng Tan, Zhangyang Gao, Jun Xia, 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

AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB.

Zhangyang Gao, Cheng Tan, Stan Z. Li

CoRR, 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

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

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

2021

Extensive Deep Temporal Point Process.

Haitao Lin, Cheng Tan, Lirong Wu, Zhangyang Gao, 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

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

A Data Augmentation Method Based on Generative Adversarial Networks for Grape Leaf Disease Identification.

Bin Liu, Cheng Tan, Shuqin Li, Jinrong He, Hongyan Wang

IEEE Access, 2020