| Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data Y Zhu, N Zabaras, PS Koutsourelakis, P Perdikaris Journal of Computational Physics 394, 56-81, 2019 | 910 | 2019 |
| Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification Y Zhu, N Zabaras Journal of Computational Physics 366, 415-447, 2018 | 677 | 2018 |
| Deep convolutional encoder‐decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media S Mo, Y Zhu, N Zabaras, X Shi, J Wu Water Resources Research 55 (1), 703-728, 2019 | 294 | 2019 |
| A poisson-gaussian denoising dataset with real fluorescence microscopy images Y Zhang*, Y Zhu*, E Nichols, Q Wang, S Zhang, C Smith, S Howard Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 185 | 2019 |
| Transformer-based transform coding Y Zhu*, Y Yang*, T Cohen International Conference on Learning Representations, 2022 | 105 | 2022 |
| Openshape: Scaling up 3d shape representation towards open-world understanding M Liu, R Shi, K Kuang, Y Zhu, X Li, S Han, H Cai, F Porikli, H Su Advances in neural information processing systems 36, 2024 | 51 | 2024 |
| Real-time image denoising of mixed Poisson–Gaussian noise in fluorescence microscopy images using ImageJ V Mannam, Y Zhang, Y Zhu, E Nichols, Q Wang, V Sundaresan, S Zhang, ... Optica 9 (4), 335-345, 2022 | 40 | 2022 |
| Partslip: Low-shot part segmentation for 3d point clouds via pretrained image-language models M Liu, Y Zhu, H Cai, S Han, Z Ling, F Porikli, H Su Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 37 | 2023 |
| Progressive neural image compression with nested quantization and latent ordering Y Lu*, Y Zhu*, Y Yang*, A Said, TS Cohen 2021 IEEE International Conference on Image Processing (ICIP), 539-543, 2021 | 24 | 2021 |
| Transform network architectures for deep learning based end-to-end image/video coding in subsampled color spaces HE Egilmez, AK Singh, M Coban, M Karczewicz, Y Zhu, Y Yang, A Said, ... IEEE Open Journal of Signal Processing 2, 441-452, 2021 | 16 | 2021 |
| Factorized inverse path tracing for efficient and accurate material-lighting estimation L Wu, R Zhu, MB Yaldiz, Y Zhu, H Cai, J Matai, F Porikli, TM Li, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 8 | 2023 |
| Performance guaranteed human-robot collaboration through correct-by-design X Zhang, Y Zhu, H Lin 2016 American Control Conference (ACC), 6183-6188, 2016 | 7 | 2016 |
| Learned B-frame compression R Pourreza, Y Yang, A Said, ZHU Yinhao, TS Cohen US Patent 11,399,198, 2022 | 2 | 2022 |
| Real-Time and Accurate Self-Supervised Monocular Depth Estimation on Mobile Device H Cai, F Yin, T Singhal, S Pendyam, P Noorzad, Y Zhu, K Nguyen, J Matai, ... NeurIPS 2021 Competitions and Demonstrations Track, 308-313, 2022 | 2 | 2022 |
| Futuredepth: Learning to predict the future improves video depth estimation R Yasarla, MK Singh, H Cai, Y Shi, J Jeong, Y Zhu, S Han, R Garrepalli, ... arXiv preprint arXiv:2403.12953, 2024 | 1 | 2024 |
| Neural image compression with controllable spatial bit allocation Y Yang, HCM LE, ZHU Yinhao, R Pourreza, A Said, Y Zhang, TS Cohen US Patent App. 17/987,844, 2023 | 1 | 2023 |
| Multi-scale optical flow for learned video compression R Pourreza, A Said, Y Yang, ZHU Yinhao, TS Cohen US Patent 11,638,025, 2023 | 1 | 2023 |
| Progressive data compression using artificial neural networks Y Lu, Y Yang, ZHU Yinhao, A Said, TS Cohen US Patent 12,008,731, 2024 | | 2024 |
| Scaling for depth estimation H Cai, ZHU Yinhao, J Jeong, SHI Yunxiao, FM Porikli US Patent App. 18/481,050, 2024 | | 2024 |
| Three-dimensional object part segmentation using a machine learning model M Liu, ZHU Yinhao, H Cai, FM Porikli, H Su US Patent App. 18/177,028, 2024 | | 2024 |
Nicholas ZabarasProfessor, Cornell University在 nd.edu 的电子邮件经过验证
