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Explainable survival analysis with uncertainty using convolution-involved vision transformer.

Z. Tang, L. Liu, Y. Shen, Z. Chen, G. Ma, J. Dong, X. Sun, X. Zhang, C. Li, Q. Zheng, и L. Yang. Comput. Medical Imaging Graph., (декабря 2023)

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Li Li

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Network embedding by fusing multimodal contents and links.F. Huang, X. Zhang, J. Xu, C. Li, и Z. Li. Knowl. Based Syst., (2019)EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing.Q. Feng, P. Li, Z. Lu, C. Li, Z. Wang, Z. Liu, C. Duan, и F. Huang. CoRR, (2022)FineFake: A Knowledge-Enriched Dataset for Fine-Grained Multi-Domain Fake News Detection.Z. Zhou, X. Zhang, L. Zhang, J. Liu, X. Zhang, и C. Li. CoRR, (2024)Hubness-aware User Identity Linkage.C. Li, S. Wang, F. Huang, J. Xu, и P. Yu. CIKM, стр. 3196-3200. ACM, (2021)Going Deeper into Permutation-Sensitive Graph Neural Networks.Z. Huang, Y. Wang, C. Li, и H. He. ICML, том 162 из Proceedings of Machine Learning Research, стр. 9377-9409. PMLR, (2022)Detecting Context Dependent Messages in a Conversational Environment.C. Li, Y. Wu, W. Wu, C. Xing, Z. Li, и M. Zhou. COLING, стр. 1990-1999. ACL, (2016)Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks.J. Yin, C. Li, H. Yan, J. Lian, и S. Wang. NeurIPS, (2023)Clean-label Poisoning Attack against Fake News Detection Models.J. Liang, X. Zhang, Y. Shang, S. Guo, и C. Li. IEEE Big Data, стр. 3614-3623. IEEE, (2023)TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems.P. Zhang, Y. Yan, X. Zhang, C. Li, S. Wang, F. Huang, и S. Kim. SIGIR, стр. 1285-1295. ACM, (2024)GPT4Rec: Graph Prompt Tuning for Streaming Recommendation.P. Zhang, Y. Yan, X. Zhang, L. Kang, C. Li, F. Huang, S. Wang, и S. Kim. SIGIR, стр. 1774-1784. ACM, (2024)

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Li Li

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Li Li

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