| Improved Peptide Retention Time Prediction in Liquid Chromatography through Deep Learning C Ma, Y Ren, J Yang, Z Ren, H Yang, S Liu Analytical chemistry 90 (18), 10881-10888, 2018 | 111 | 2018 |
| Scribble-based hierarchical weakly supervised learning for brain tumor segmentation Z Ji, Y Shen, C Ma, M Gao Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 46 | 2019 |
| Neural style transfer improves 3d cardiovascular mr image segmentation on inconsistent data C Ma, Z Ji, M Gao Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 41 | 2019 |
| DeepRT: deep learning for peptide retention time prediction in proteomics C Ma, Z Zhu, J Ye, J Yang, J Pei, S Xu, R Zhou, C Yu, F Mo, B Wen, S Liu arXiv preprint arXiv:1705.05368, 2017 | 13 | 2017 |
| Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimization C Ma, Z Huang, J Xian, M Gao, J Xu Uncertainty in Artificial Intelligence, 75-85, 2021 | 7 | 2021 |
| Improvement of peptide identification with considering the abundance of mRNA and peptide C Ma, S Xu, G Liu, X Liu, X Xu, B Wen, S Liu BMC bioinformatics 18, 1-8, 2017 | 6 | 2017 |
| Few-shot Learning via Dirichlet Tessellation Ensemble C Ma, Z Huang, M Gao, J Xu International Conference on Learning Representations, 2021 | 5 | 2021 |
| DeepQuality: Mass Spectra Quality Assessment via Compressed Sensing and Deep Learning C Ma arXiv preprint arXiv:1710.11430, 2017 | 5 | 2017 |
| Few-shot Learning as Cluster-induced Voronoi Diagrams: A Geometric Approach C Ma, Z Huang, M Gao, J Xu arXiv preprint arXiv:2202.02471, 2022 | 2 | 2022 |
| Retention Time of Peptides in Liquid Chromatography Is Well Estimated upon Deep Transfer Learning C Ma, Z Zhu, J Ye, J Yang, J Pei, S Xu, C Yu, F Mo, B Wen, S Liu arXiv preprint arXiv:1711.00045, 2017 | 1 | 2017 |
| FedMM: A Communication Efficient Solver for Federated Adversarial Domain Adaptation Y Shen, J Du, H Zhao, Z Ji, C Ma, M Gao Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023 | | 2023 |
| Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning C Ma, Z Ji, Z Huang, Y Shen, M Gao, J Xu The Eleventh International Conference on Learning Representations, 2023 | | 2023 |
| Few-Shot Learning Geometric Ensemble for Multi-label Classification of Chest X-Rays D Moukheiber, S Mahindre, L Moukheiber, M Moukheiber, S Wang, C Ma, ... Data Augmentation, Labelling, and Imperfections: Second MICCAI Workshop …, 2022 | | 2022 |
| Progressive Voronoi Diagram Subdivision: Towards A Holistic Geometric Framework for Exemplar-free Class-Incremental Learning C Ma, Z Ji, Z Huang, Y Shen, M Gao, J Xu arXiv preprint arXiv:2207.14202, 2022 | | 2022 |
| A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning Y Shen, Z Ji, C Ma, M Gao arXiv preprint arXiv:2205.02371, 2022 | | 2022 |
| A Stochastic Gradient Langevin Dynamics Algorithm For Noise Intrinsic Federated Learning Y Shen, J Du, C Ma, M Gao, B Zhang ICLR 2021 Submission, 2020 | | 2020 |
| Weakly-Supervised Brain Tumor Classification with Global Diagnosis Label Y Zhou, Z Li, C Ma, C Chen, M Gao, H Zhu, J Xu 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1-5, 2020 | | 2020 |
Jinhui XuProfessor of the State University of New York at BuffaloVerified email at buffalo.edu
