| An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization Y Shen, N Wu, J Phang, J Park, K Liu, S Tyagi, L Heacock, SG Kim, L Moy, ... Medical image analysis 68, 101908, 2021 | 178 | 2021 |
| Adaptive Early-Learning Correction for Segmentation from Noisy Annotations S Liu*, K Liu*, (*equal contribution order by coin clip), WZ Zhu, Y Shen, ... CVPR 2022 (Oral), 2022 | 111 | 2022 |
| Are All Losses Created Equal: A Neural Collapse Perspective J Zhou, C You, X Li, K Liu, S Liu, Q Qu, Z Zhu NeurIPS, 2022 | 53 | 2022 |
| Optimal operation strategy for distributed battery aggregator providing energy and ancillary services K Liu, Q Chen, C Kang, W Su, G Zhong Journal of Modern Power Systems and Clean Energy 6 (4), 722-732, 2018 | 47 | 2018 |
| Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis K Liu, Y Shen, N Wu, J Chłędowski, C Fernandez-Granda, KJ Geras Medical Imaging with Deep Learning 2021, 2021 | 32 | 2021 |
| Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning K Liu*, W Zhu*, Y Shen, S Liu, N Razavian, K J. Geras, ... CVPR 2023 (https://arxiv.org/abs/2210.09452), 2023 | 27 | 2023 |
| K2S challenge: From undersampled K-space to automatic segmentation AA Tolpadi, U Bharadwaj, KT Gao, R Bhattacharjee, FG Gassert, ... Bioengineering 10 (2), 267, 2023 | 17 | 2023 |
| Cram\'er-Rao bound-informed training of neural networks for quantitative MRI X Zhang*, Q Duchemin*, K Liu*, S Flassbeck, C Gultekin, ... Magnetic resonance in medicine, 2022 | 12 | 2022 |
| StrokeRehab: A Benchmark Dataset for Sub-second Action Identification A Kaku*, K Liu*, A Parnandi*, HR Rajamohan, K Venkataramanan, ... NeurIPS, 2022 | 7 | 2022 |
| Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning K Liu*, S Gu*, A Romero, R Timofte, (*equal contribution) Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 7 | 2021 |
| Rapid quantitative magnetization transfer imaging: Utilizing the hybrid state and the generalized Bloch model J Assländer, C Gultekin, A Mao, X Zhang, Q Duchemin, K Liu, ... Magnetic resonance in medicine 91 (4), 1478-1497, 2024 | 6 | 2024 |
| Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution A Kaku*, K Liu*, A Parnandi*, HR Rajamohan, K Venkataramanan, ... https://arxiv.org/abs/2111.02521, 2021 | 6 | 2021 |
| Optimized dimensionality reduction for parameter estimation in MR fingerprinting via deep learning Q Duchemin, K Liu, C Fernandez-Granda, J Assländer | 3 | 2021 |
| Controllable One-Shot Face Video Synthesis With Semantic Aware Prior K Liu, YC Su, WA Hong, R Cang, X Jia https://arxiv.org/abs/2304.14471, 2023 | 2 | 2023 |
| Quantifying impairment and disease severity using AI models trained on healthy subjects B Yu, A Kaku, K Liu, A Parnandi, E Fokas, A Venkatesan, N Pandit, ... npj Digital Medicine 7 (1), 180, 2024 | 1 | 2024 |
| Multi-modal AI for comprehensive breast cancer prognostication J Witowski, K Zeng, J Cappadona, J Elayoubi, ED Chiru, N Chan, ... arXiv preprint arXiv:2410.21256, 2024 | | 2024 |
| Navigating the Challenges of Imperfect Supervision for Machine Learning in the Real-World K Liu New York University, 2024 | | 2024 |
| Uncertainty-aware Fine-tuning of Segmentation Foundation Models K Liu, B Price, J Kuen, Y Fan, Z Wei, L Figueroa, K J. Geras, ... NeurIPS, 2024 | | 2024 |
