Pei Liu
Orcid: 0000-0002-3795-6140Affiliations:
- University of Electronic Science and Technology of China, School of Computer Science and Engineering, Big Data Research Center, Chengdu, China
According to our database1,
Pei Liu authored at least 20 papers
between 2019 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
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on orcid.org
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Bibliography
2026
Sparse Task Vector Mixup with Hypernetworks for Efficient Knowledge Transfer in Whole-Slide Image Prognosis.
CoRR, March, 2026
CAML: A Conflict-Aware Molecular Language Model Merging Framework for Multi-Constraint Molecular Generation.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026
2025
Towards Understanding and Harnessing the Transferability of Prognostic Knowledge in Computational Pathology.
CoRR, August, 2025
WSOE: Weakly Supervised Outlier Exposure for Object-level Out-of-distribution detection.
Expert Syst. Appl., 2025
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
2024
Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification.
IEEE Trans. Medical Imaging, May, 2024
AdvMIL: Adversarial multiple instance learning for the survival analysis on whole-slide images.
Medical Image Anal., January, 2024
ProDiv: Prototype-driven consistent pseudo-bag division for whole-slide image classification.
Comput. Methods Programs Biomed., 2024
Collaborative Learning with Curriculum Loss for Accurate and Interpretable Weakly Supervised Whole-Slide Image Classification.
Proceedings of 2024 International Conference on Machine Learning and Intelligent Computing (MLIC 2024), 2024
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
DSCA: A dual-stream network with cross-attention on whole-slide image pyramids for cancer prognosis.
Expert Syst. Appl., October, 2023
GraphLSurv: A scalable survival prediction network with adaptive and sparse structure learning for histopathological whole-slide images.
Comput. Methods Programs Biomed., April, 2023
ProtoDiv: Prototype-guided Division of Consistent Pseudo-bags for Whole-slide Image Classification.
CoRR, 2023
2022
Dual-Stream Transformer with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis.
CoRR, 2022
DeepGCNMIL: Multi-head Attention Guided Multi-Instance Learning Approach for Whole-Slide Images Survival Analysis Using Graph Convolutional Networks.
Proceedings of the ICMLC 2022: 14th International Conference on Machine Learning and Computing, Guangzhou, China, February 18, 2022
2021
Optimizing Survival Analysis of XGBoost for Ties to Predict Disease Progression of Breast Cancer.
IEEE Trans. Biomed. Eng., 2021
2019
Predicting Invasive Disease-Free Survival for Early Stage Breast Cancer Patients Using Follow-Up Clinical Data.
IEEE Trans. Biomed. Eng., 2019
HitBoost: Survival Analysis via a Multi-Output Gradient Boosting Decision Tree Method.
IEEE Access, 2019