| Can contrastive learning avoid shortcut solutions? J Robinson, L Sun, K Yu, K Batmanghelich, S Jegelka, S Sra NeurIPS 2021 34, 4974-4986, 2021 | 116 | 2021 |
| Hierarchical amortized GAN for 3D high resolution medical image synthesis L Sun, J Chen, Y Xu, M Gong, K Yu, K Batmanghelich IEEE journal of biomedical and health informatics 26 (8), 3966-3975, 2022 | 56 | 2022 |
| Monitoring ICU mortality risk with a long short-term memory recurrent neural network K Yu, M Zhang, T Cui, M Hauskrecht PSB 2020, 103-114, 2019 | 52 | 2019 |
| Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space K Yu, S Visweswaran, K Batmanghelich Journal of Chemical Information and Modeling, 2020 | 25 | 2020 |
| Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays K Yu, S Ghosh, Z Liu, C Deible, K Batmanghelich MICCAI 2022, 2022 | 22 | 2022 |
| Context Matters: Graph-based Self-supervised Representation Learning for Medical Images L Sun*, K Yu*, K Batmanghelich AAAI 2021, 2021 | 21 | 2021 |
| Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN L Sun, J Chen, Y Xu, M Gong, K Yu, K Batmanghelich 34th Neural Information Processing Systems, NeurIPS Workshop, 2020 | 12 | 2020 |
| Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat S Ghosh, K Yu, F Arabshahi, K Batmanghelich ICML 2023 202, 11360--11397, 2023 | 8* | 2023 |
| De novo prediction of Cell-Drug sensitivities using deep learning-based graph regularized matrix factorization S Ren, Y Tao, K Yu, Y Xue, R Schwartz, X Lu PSB 2022, 278-289, 2021 | 6 | 2021 |
| DrasCLR: A self-supervised framework of learning disease-related and anatomy-specific representation for 3D lung CT images K Yu, L Sun, J Chen, M Reynolds, T Chaudhary, K Batmanghelich Medical Image Analysis 92, 103062, 2024 | 4 | 2024 |
| Missing Pavement Performance Data Imputation Using Graph Neural Networks L Gao, K Yu, P Lu TRR 2022, 2022 | 4 | 2022 |
| Distilling BlackBox to Interpretable models for Efficient Transfer Learning S Ghosh, K Yu, K Batmanghelich MICCAI 2023, 2023 | 2 | 2023 |
| Deep learning integration of chest computed tomography imaging and gene expression identifies novel aspects of COPD J Chen, Z Xu, L Sun, K Yu, CP Hersh, A Boueiz, JE Hokanson, FC Sciurba, ... Chronic Obstructive Pulmonary Diseases: Journal of the COPD Foundation 10 (4 …, 2023 | 2* | 2023 |
| Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network K Yu, L Sun, K Batmanghelich 34th Neural Information Processing Systems, NeurIPS Workshop, 2020 | 2 | 2020 |
| Development of temporal context-based feature abstractions for enabling monitoring and managing of interventions PYS Hsueh, S Ramakrishnan, K Yu, M Akushevich, S Sharma, ... e-Health–For Continuity of Care, 471-475, 2014 | 2 | 2014 |
| Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling K Yu, S Albro, G DeSalvo, S Kothawade, A Rashwan, S Tavakkol, ... ICCV 2023 Workshop on Uncertainty Quantification for Computer Vision, 2023 | 1 | 2023 |
| Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics N Murali, AM Puli, K Yu, R Ranganath, K Batmanghelich Transactions on Machine Learning Research, 2023 | 1 | 2023 |
| Shortcut Learning Through the Lens of Early Training Dynamics N Murali, AM Puli, K Yu, R Ranganath, K Batmanghelich ICML 2023 Workshop on Spurious Correlations, Invariance and Stability, 2023 | 1 | 2023 |
| Tackling Shortcut Learning in Deep Neural Networks: An Iterative Approach with Interpretable Models BK Shantanu Ghosh, Ke Yu, Forough Arabshahi ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability …, 2023 | 1* | 2023 |
| Boosting the interpretability of clinical risk scores with intervention predictions E Loreaux*, K Yu*, J Kemp, M Seneviratne, C Chen, S Yadlowsky, ... KDD 2022 Workshop on DSHealth, 2022 | 1 | 2022 |
Kayhan BatmanghelichAssistant Professor, Boston University在 bu.edu 的电子邮件经过验证
