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Journal Articles
- 2021
[j3]Zhen Chen
, Yuli Fu, Youjun Xiang, Yinhao Zhu:
A novel MR image denoising via LRMA and NLSS. Signal Process. 185: 108109 (2021)- 2019
- [j2]Yinhao Zhu, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis, Paris Perdikaris:
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data. J. Comput. Phys. 394: 56-81 (2019) - 2018
- [j1]Yinhao Zhu, Nicholas Zabaras:
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification. J. Comput. Phys. 366: 415-447 (2018)
Conference and Workshop Papers
- 2023
- [c8]Minghua Liu, Yinhao Zhu, Hong Cai, Shizhong Han, Zhan Ling, Fatih Porikli, Hao Su:
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models. CVPR 2023: 21736-21746 - [c7]Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, Hong Cai, Janarbek Matai, Fatih Porikli, Tzu-Mao Li, Manmohan Chandraker, Ravi Ramamoorthi:
Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. ICCV 2023: 3825-3835 - [c6]Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, Hao Su:
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding. NeurIPS 2023 - 2022
- [c5]Yinhao Zhu, Yang Yang, Taco Cohen:
Transformer-based Transform Coding. ICLR 2022 - 2021
- [c4]Yadong Lu, Yinhao Zhu, Yang Yang, Amir Said, Taco S. Cohen:
Progressive Neural Image Compression With Nested Quantization And Latent Ordering. ICIP 2021: 539-543 - [c3]Hong Cai, Fei Yin, Tushar Singhal, Sandeep Pendyam, Parham Noorzad, Yinhao Zhu, Khoi Nguyen, Janarbek Matai, Bharath Ramaswamy, Frank Mayer, Chirag Patel, Abhijit Khobare, Fatih Porikli:
Real-Time and Accurate Self-Supervised Monocular Depth Estimation on Mobile Device. NeurIPS (Competition and Demos) 2021: 308-313 - 2019
- [c2]Yide Zhang, Yinhao Zhu, Evan L. Nichols, Qingfei Wang, Siyuan Zhang, Cody J. Smith, Scott S. Howard:
A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy Images. CVPR 2019: 11710-11718 - 2016
- [c1]Xiaobin Zhang, Yinhao Zhu, Hai Lin:
Performance guaranteed human-robot collaboration through correct-by-design. ACC 2016: 6183-6188
Informal and Other Publications
- 2024
- [i11]Farhad G. Zanjani, Hong Cai, Yinhao Zhu, Leyla Mirvakhabova, Fatih Porikli:
Neural Mesh Fusion: Unsupervised 3D Planar Surface Understanding. CoRR abs/2402.16739 (2024) - [i10]Rajeev Yasarla, Manish Kumar Singh, Hong Cai, Yunxiao Shi, Jisoo Jeong, Yinhao Zhu, Shizhong Han, Risheek Garrepalli, Fatih Porikli:
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation. CoRR abs/2403.12953 (2024) - 2023
- [i9]Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, Hong Cai, Janarbek Matai, Fatih Porikli, Tzu-Mao Li, Manmohan Chandraker, Ravi Ramamoorthi:
Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. CoRR abs/2304.05669 (2023) - [i8]Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, Hao Su:
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding. CoRR abs/2305.10764 (2023) - 2022
- [i7]Minghua Liu, Yinhao Zhu, Hong Cai, Shizhong Han, Zhan Ling, Fatih Porikli, Hao Su:
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models. CoRR abs/2212.01558 (2022) - 2021
- [i6]Yadong Lu, Yinhao Zhu, Yang Yang, Amir Said, Taco S. Cohen:
Progressive Neural Image Compression with Nested Quantization and Latent Ordering. CoRR abs/2102.02913 (2021) - [i5]Hilmi E. Egilmez, Ankitesh K. Singh, Muhammed Z. Coban, Marta Karczewicz, Yinhao Zhu, Yang Yang, Amir Said, Taco S. Cohen:
Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces. CoRR abs/2103.01760 (2021) - 2019
- [i4]Yinhao Zhu, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis, Paris Perdikaris:
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data. CoRR abs/1901.06314 (2019) - 2018
- [i3]Yinhao Zhu, Nicholas Zabaras:
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification. CoRR abs/1801.06879 (2018) - [i2]Shaoxing Mo, Yinhao Zhu, Nicholas Zabaras, Xiaoqing Shi, Jichun Wu:
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media. CoRR abs/1807.00882 (2018) - [i1]Yide Zhang, Yinhao Zhu, Evan L. Nichols, Qingfei Wang, Siyuan Zhang, Cody J. Smith, Scott S. Howard:
A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy Images. CoRR abs/1812.10366 (2018)
Coauthor Index
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