Jun Xia

According to our database, Jun Xia authored at least 42 papers between 2020 and 2024.

Collaborative distances:

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

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

NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics.

Jingbo Zhou, Shaorong Chen, Jun Xia, Sizhe Liu, Tianze Ling, Wenjie Du, Yue Liu, Jianwei Yin, Stan Z. Li

CoRR, 2024

AdaNovo: Adaptive \emph{De Novo} Peptide Sequencing with Conditional Mutual Information.

Jun Xia, Shaorong Chen, Jingbo Zhou, Tianze Ling, Wenjie Du, Sizhe Liu, Stan Z. Li

CoRR, 2024

Graph-level Protein Representation Learning by Structure Knowledge Refinement.

Ge Wang, Zelin Zang, Jiangbin Zheng, Jun Xia, 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 Graph is Worth K Words: Euclideanizing Graph using Pure Transformer.

Zhangyang Gao, Daize Dong, Cheng Tan, Jun Xia, Bozhen Hu, 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

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

Zhangyang Gao, Cheng Tan, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DiscoGNN: A Sample-Efficient Framework for Self-Supervised Graph Representation Learning.

Jun Xia, Shaorong Chen, Yue Liu, Zhangyang Gao, Jiangbin Zheng, Xihong Yang, Stan Z. Li

Proceedings of the 40th IEEE International Conference on Data Engineering, 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

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

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

Why Deep Models Often cannot Beat Non-deep Counterparts on Molecular Property Prediction?

Jun Xia, Lecheng Zhang, Xiao Zhu, Stan Z. Li

CoRR, 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

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

Reinforcement Graph Clustering with Unknown Cluster Number.

Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, Stan Z. Li

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

A Systematic Survey of Chemical Pre-trained Models.

Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Dink-Net: Neural Clustering on Large Graphs.

Yue Liu, Ke Liang, Jun Xia, Sihang Zhou, Xihong Yang, Xinwang Liu, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 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

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

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

A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application.

Yue Liu, Jun Xia, Sihang Zhou, Siwei Wang, Xifeng Guo, Xihong Yang, Ke Liang, Wenxuan Tu, Stan Z. Li, Xinwang Liu

CoRR, 2022

A Systematic Survey of Molecular Pre-trained Models.

Jun Xia, Yanqiao Zhu, Yuanqi Du, Yue Liu, 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

Generative De Novo Protein Design with Global Context.

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

CoRR, 2022

A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications.

Jun Xia, Yanqiao Zhu, Yuanqi Du, 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

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

Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings.

Jiangbin Zheng, Yile Wang, Ge Wang, Jun Xia, Yufei Huang, Guojiang Zhao, Yue Zhang, Stan Z. Li

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Debiased Graph Contrastive Learning.

Jun Xia, Lirong Wu, Jintao Chen, Ge Wang, 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

Deep Clustering and Representation Learning that Preserves Geometric Structures.

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

CoRR, 2020