| Adabelief optimizer: Adapting stepsizes by the belief in observed gradients J Zhuang, T Tang, Y Ding, SC Tatikonda, N Dvornek, X Papademetris, ... Advances in neural information processing systems 33, 18795-18806, 2020 | 569 | 2020 |
| Braingnn: Interpretable brain graph neural network for fmri analysis X Li, Y Zhou, N Dvornek, M Zhang, S Gao, J Zhuang, D Scheinost, ... Medical Image Analysis 74, 102233, 2021 | 426 | 2021 |
| Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results X Li, Y Gu, N Dvornek, LH Staib, P Ventola, JS Duncan Medical image analysis 65, 101765, 2020 | 375 | 2020 |
| Identifying autism from resting-state fMRI using long short-term memory networks NC Dvornek, P Ventola, KA Pelphrey, JS Duncan Machine Learning in Medical Imaging: 8th International Workshop, MLMI 2017 …, 2017 | 252 | 2017 |
| Unsupervised domain adaptation via disentangled representations: Application to cross-modality liver segmentation J Yang, NC Dvornek, F Zhang, J Chapiro, MD Lin, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 153 | 2019 |
| ShelfNet for real-time semantic segmentation J Zhuang, J Yang, L Gu, NC Dvornek arXiv preprint arXiv:1811.11254, 2018 | 148* | 2018 |
| Surrogate gap minimization improves sharpness-aware training J Zhuang, B Gong, L Yuan, Y Cui, H Adam, N Dvornek, S Tatikonda, ... arXiv preprint arXiv:2203.08065, 2022 | 123 | 2022 |
| Adaptive checkpoint adjoint method for gradient estimation in neural ode J Zhuang, N Dvornek, X Li, S Tatikonda, X Papademetris, J Duncan International Conference on Machine Learning, 11639-11649, 2020 | 121 | 2020 |
| Brain responses to biological motion predict treatment outcome in young children with autism D Yang, KA Pelphrey, DG Sukhodolsky, MJ Crowley, E Dayan, ... Translational psychiatry 6 (11), e948-e948, 2016 | 118 | 2016 |
| Graph neural network for interpreting task-fmri biomarkers X Li, NC Dvornek, Y Zhou, J Zhuang, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 111 | 2019 |
| Combining phenotypic and resting-state fMRI data for autism classification with recurrent neural networks NC Dvornek, P Ventola, JS Duncan 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 86 | 2018 |
| 2-channel convolutional 3D deep neural network (2CC3D) for fMRI analysis: ASD classification and feature learning X Li, NC Dvornek, X Papademetris, J Zhuang, LH Staib, P Ventola, ... 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 80 | 2018 |
| Brain biomarker interpretation in ASD using deep learning and fMRI X Li, NC Dvornek, J Zhuang, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 80 | 2018 |
| Pooling regularized graph neural network for fmri biomarker analysis X Li, Y Zhou, NC Dvornek, M Zhang, J Zhuang, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 71 | 2020 |
| Fedni: Federated graph learning with network inpainting for population-based disease prediction L Peng, N Wang, N Dvornek, X Zhu, X Li IEEE Transactions on Medical Imaging 42 (7), 2032-2043, 2022 | 64 | 2022 |
| Non-rigid registration with missing correspondences in preoperative and postresection brain images N Chitphakdithai, JS Duncan International Conference on Medical Image Computing and Computer-Assisted …, 2010 | 60 | 2010 |
| Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder A Venkataraman, DYJ Yang, N Dvornek, LH Staib, JS Duncan, ... Neuroreport 27 (14), 1081-1085, 2016 | 56 | 2016 |
| Mali: A memory efficient and reverse accurate integrator for neural odes J Zhuang, NC Dvornek, S Tatikonda, JS Duncan arXiv preprint arXiv:2102.04668, 2021 | 54 | 2021 |
| Learning generalizable recurrent neural networks from small task-fmri datasets NC Dvornek, D Yang, P Ventola, JS Duncan International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 41 | 2018 |
| Efficient Shapley explanation for features importance estimation under uncertainty X Li, Y Zhou, NC Dvornek, Y Gu, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 34 | 2020 |
James S. DuncanEbenezer K. Hunt Professor of Biomedical Engineering, Radiology, Electr. Engr., Yale University在 yale.edu 的电子邮件经过验证
