Yunfan Li

Orcid: 0000-0002-0965-8445

Affiliations:
  • Sichuan University, College of Computer Science, Chengdu, China


According to our database1, Yunfan Li authored at least 14 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Single-Cell RNA-Seq Debiased Clustering via Batch Effect Disentanglement.
IEEE Trans. Neural Networks Learn. Syst., August, 2024

Cross-Modal Retrieval With Noisy Correspondence via Consistency Refining and Mining.
IEEE Trans. Image Process., 2024

A Survey on Deep Clustering: From the Prior Perspective.
CoRR, 2024

Image Clustering with External Guidance.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Test-time Adaptation against Multi-modal Reliability Bias.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Robust Multi-View Clustering With Incomplete Information.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Incomplete Multi-view Clustering via Prototype-based Imputation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
XAI Beyond Classification: Interpretable Neural Clustering.
J. Mach. Learn. Res., 2022

Twin Contrastive Learning for Online Clustering.
Int. J. Comput. Vis., 2022

Deep Fair Clustering via Maximizing and Minimizing Mutual Information.
CoRR, 2022

2021
Partially View-Aligned Representation Learning With Noise-Robust Contrastive Loss.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Contrastive Clustering.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021


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