conST: an interpretable multi-modal contrastive learning framework for spatial transcriptomics Y Zong, T Yu, X Wang, Y Wang, Z Hu, Y Li BioRxiv, 2022.01. 14.476408, 2022 | 23 | 2022 |
Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration X Wang, Z Hu, T Yu, Y Wang, R Wang, Y Wei, J Shu, J Ma, Y Li Bioinformatics 39 (4), btad162, 2023 | 10 | 2023 |
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models Y Zong, O Bohdal, T Yu, Y Yang, T Hospedales arXiv preprint arXiv:2402.02207, 2024 | 5 | 2024 |
Fool your (vision and) language model with embarrassingly simple permutations Y Zong, T Yu, B Zhao, R Chavhan, T Hospedales arXiv preprint arXiv:2310.01651, 2023 | 2 | 2023 |
scMinerva: an Unsupervised Graph Learning Framework with Label-efficient Fine-tuning for Single-cell Multi-omics Integrated Analysis T Yu, Y Zong, Y Wang, X Wang, Y Li bioRxiv, 2022.05. 28.493838, 2022 | | 2022 |
scMinerva: a GCN-featured Interpretable Framework for Single-cell Multi-omics Integration with Random Walk on Heterogeneous Graph YU Tingyang, Y Zong, Y Wang, X Wang, Y Li | | |
Projection Robust Optimal Transport Between Unbalanced Distributions T Yu, Y Wan, S Ma | | |
Subgraph Sampling Strategy for Equivariant Subgraph Aggregation Network Based on Weisfeiler-Lehman Similarity Y Tingyang | | |