Performance guaranteed human-robot collaboration through correct-by-design. - Xiaobin Zhang; Yinhao Zhu; Hai Lin (ACC, 2016)

Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media. - Shaoxing Mo; Yinhao Zhu; Nicholas Zabaras; Xiaoqing Shi; Jichun Wu (CoRR, 2018)

Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification. - Yinhao Zhu; Nicholas Zabaras (J. Comput. Phys., 2018)

A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy Images. - Yide Zhang; Yinhao Zhu; Evan L. Nichols; Qingfei Wang; Siyuan Zhang; Cody J. Smith; Scott S. Howard (CVPR, 2019)

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data. - Yinhao Zhu; Nicholas Zabaras; Phaedon-Stelios Koutsourelakis; Paris Perdikaris (J. Comput. Phys., 2019)

Progressive Neural Image Compression With Nested Quantization And Latent Ordering. - Yadong Lu; Yinhao Zhu; Yang Yang 010; Amir Said; Taco S. Cohen (ICIP, 2021)

Real-Time and Accurate Self-Supervised Monocular Depth Estimation on Mobile Device. - Hong Cai; Fei Yin; Tushar Singhal; Sandeep Pendyam; Parham Noorzad; Yinhao Zhu; Khoi Nguyen; Janarbek Matai; Bharath Ramaswamy; Frank Mayer; Chirag Patel; Abhijit Khobare; et al. (NeurIPS (Competition and Demos), 2021)

Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces. - Hilmi E. Egilmez; Ankitesh K. Singh; Muhammed Z. Coban; Marta Karczewicz; Yinhao Zhu; Yang Yang 010; Amir Said; Taco S. Cohen (CoRR, 2021)

A novel MR image denoising via LRMA and NLSS. - Zhen Chen 010; Yuli Fu 001; Youjun Xiang; Yinhao Zhu (Signal Process., 2021)

Transformer-based Transform Coding. - Yinhao Zhu; Yang Yang 010; Taco Cohen (ICLR, 2022)

PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models. - Minghua Liu; Yinhao Zhu; Hong Cai; Shizhong Han; Zhan Ling; Fatih Porikli; Hao Su 001 (CVPR, 2023)

Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. - Liwen Wu; Rui Zhu; Mustafa B. Yaldiz; Yinhao Zhu; Hong Cai; Janarbek Matai; Fatih Porikli; Tzu-Mao Li; Manmohan Chandraker; Ravi Ramamoorthi (ICCV, 2023)

OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding. - Minghua Liu; Ruoxi Shi; Kaiming Kuang; Yinhao Zhu; Xuanlin Li; Shizhong Han; Hong Cai; Fatih Porikli; Hao Su 001 (NeurIPS, 2023)

FutureDepth: Learning to Predict the Future Improves Video Depth Estimation. - Rajeev Yasarla; Manish Kumar Singh 002; Hong Cai; Yunxiao Shi; Jisoo Jeong; Yinhao Zhu; Shizhong Han; Risheek Garrepalli; Fatih Porikli (ECCV (5), 2024)

Neural Mesh Fusion: Unsupervised 3D Planar Surface Understanding. - Farhad G. Zanjani; Hong Cai; Yinhao Zhu; Leyla Mirvakhabova; Fatih Porikli (ICIP, 2024)

BePo: Leveraging Birds Eye View and Sparse Points for Efficient and Accurate 3D Occupancy Prediction. - Yunxiao Shi; Hong Cai; Jisoo Jeong; Yinhao Zhu; Shizhong Han; Amin Ansari; Fatih Porikli (CoRR, 2025)

ODG: Occupancy Prediction Using Dual Gaussians. - Yunxiao Shi; Yinhao Zhu; Shizhong Han; Jisoo Jeong; Amin Ansari; Hong Cai; Fatih Porikli (CoRR, 2025)