Comparative Analysis of Some Parametric Model Structures Dedicated to EDLC Diagnosis. - Emmanuel Schaeffer; François Auger; Zhihao Shi; Philippe Guillemet; Luc Loron (IEEE Trans. Ind. Electron., 2016)

GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing. - Xiaohong Liu 001; Yongrui Ma; Zhihao Shi; Jun Chen 005 (ICCV, 2019)

Video Interpolation via Generalized Deformable Convolution. - Zhihao Shi; Xiaohong Liu 001; Kangdi Shi; Linhui Dai; Jun Chen 005 (CoRR, 2020)

Learning for Unconstrained Space-Time Video Super-Resolution. - Zhihao Shi; Chengqi Li; Linhui Dai; Xiaohong Liu 001; Jun Chen 005; Timothy N. Davidson (CoRR, 2021)

GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing. - Xiaohong Liu 001; Zhihao Shi; Zijun Wu; Jun Chen 005 (CoRR, 2021)

Towards a Unified Approach to Single Image Deraining and Dehazing. - Xiaohong Liu 001; Yongrui Ma; Zhihao Shi; Linhui Dai; Jun Chen 005 (CoRR, 2021)

Lithium-Sulfur Cell State of Charge Estimation Using a Classification Technique. - Neda Shateri; Zhihao Shi; Daniel J. Auger; Abbas Fotouhi (IEEE Trans. Veh. Technol., 2021)

Video Frame Interpolation Transformer. - Zhihao Shi; Xiangyu Xu 002; Xiaohong Liu 001; Jun Chen 005; Ming-Hsuan Yang 001 (CVPR, 2022)

Learning for Unconstrained Space-Time Video Super-Resolution. - Zhihao Shi; Xiaohong Liu 001; Chengqi Li; Linhui Dai; Jun Chen 005; Timothy N. Davidson; Jiying Zhao (IEEE Trans. Broadcast., 2022)

Video Frame Interpolation via Generalized Deformable Convolution. - Zhihao Shi; Xiaohong Liu 001; Kangdi Shi; Linhui Dai; Jun Chen 005 (IEEE Trans. Multim., 2022)

LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. - Zhihao Shi; Xize Liang; Jie Wang 005 (ICLR, 2023)

Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution. - Jie Wang 005; Rui Yang; Zijie Geng; Zhihao Shi; Mingxuan Ye; Qi Zhou 008; Shuiwang Ji; Bin Li 025; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2023)

Provably Convergent Subgraph-wise Sampling for Fast GNN Training. - Jie Wang 005; Zhihao Shi; Xize Liang; Shuiwang Ji; Bin Li 025; Feng Wu 001 (CoRR, 2023)

Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction. - Jie Wang 005; Hanzhu Chen; Qitan Lv; Zhihao Shi; Jiajun Chen 001; Huarui He; Hongtao Xie; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2023)

Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias. - Zhihao Shi; Jie Wang 005; Fanghua Lu; Hanzhu Chen; Defu Lian; Zheng Wang; Jieping Ye; Feng Wu 001 (CoRR, 2023)

Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. - Jie Wang 005; Zhanqiu Zhang; Zhihao Shi; Jianyu Cai; Shuiwang Ji; Feng Wu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Enabling Trimap-Free Image Matting With a Frequency-Guided Saliency-Aware Network via Joint Learning. - Linhui Dai; Xiang Song; Xiaohong Liu 001; Chengqi Li; Zhihao Shi; Jun Chen 005; Martin Brooks (IEEE Trans. Multim., 2023)

GridDehazeNet+: An Enhanced Multi-Scale Network With Intra-Task Knowledge Transfer for Single Image Dehazing. - Xiaohong Liu 001; Zhihao Shi; Zijun Wu; Jun Chen 005; Guangtao Zhai (IEEE Trans. Intell. Transp. Syst., 2023)

TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling. - Dong Huo; Zixin Guo; Xinxin Zuo; Zhihao Shi; Juwei Lu; Peng Dai 002; Songcen Xu; Li Cheng 001; Yee-Hong Yang (ECCV (38), 2024)

An EWMA-Based Mitigation Scheme Against Interest Flooding Attacks in Named Data Networks. - Zhihao Shi; Yaozong Xu; Maode Ma; Yanan Zhang (ICIC (9), 2024)

Robust Preference Optimization with Provable Noise Tolerance for LLMs. - Xize Liang; Chao Chen 026; Jie Wang 005; Yue Wu; Zhihang Fu; Zhihao Shi; Feng Wu 001; Jieping Ye (CoRR, 2024)

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. - Jie Wang 005; Zhihai Wang; Xijun Li; Yufei Kuang; Zhihao Shi; Fangzhou Zhu; Mingxuan Yuan; Jia Zeng; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2024)

Label Deconvolution for Node Representation Learning on Large-Scale Attributed Graphs Against Learning Bias. - Zhihao Shi; Jie Wang 005; Fanghua Lu; Hanzhu Chen; Defu Lian; Zheng Wang; Jieping Ye; Feng Wu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. - Jie Wang 005; Zhihai Wang; Xijun Li; Yufei Kuang; Zhihao Shi; Fangzhou Zhu; Mingxuan Yuan; Jia Zeng; Yongdong Zhang 001; Feng Wu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

IMFine: 3D Inpainting via Geometry-guided Multi-view Refinement. - Zhihao Shi; Dong Huo; Yuhongze Zhou; Yan Min; Juwei Lu; Xinxin Zuo (CVPR, 2025)

Accurate and Scalable Graph Neural Networks via Message Invariance. - Zhihao Shi; Jie Wang 005; Zhiwei Zhuang; Xize Liang; Bin Li 025; Feng Wu 001 (ICLR, 2025)

CATI: A medical context-enhanced framework for diagnosis code assignment in the UK Biobank study. - Yue Shen; Jie Wang 005; Zhe Wang; Zhihao Shi; Hanzhu Chen; Zheng Wang; Yukang Jiang; Xiaopu Wang; Chuandong Cheng; Xueqin Wang; Hongtu Zhu; Jieping Ye (Artif. Intell. Medicine, 2025)

Development of a machine learning-based prognostic model for survival prediction in patients with lung cancer brain metastases using multicenter clinical data. - Yuyan Xie; Xuqin Xiang; Menglin Fan; Hongyan Li; Lijuan Du; Weitong Gao; Tong Chen; Zhihao Shi; Xinqi Yu; Fang Liu (Int. J. Medical Informatics, 2025)

IMFine: 3D Inpainting via Geometry-guided Multi-view Refinement. - Zhihao Shi; Dong Huo; Yuhongze Zhou; Kejia Yin; Yan Min; Juwei Lu; Xinxin Zuo (CoRR, 2025)

Robust Neural Rendering in the Wild with Asymmetric Dual 3D Gaussian Splatting. - Chengqi Li; Zhihao Shi; Yangdi Lu; Wenbo He; Xiangyu Xu (CoRR, 2025)