Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (CoRR, 2021)

Approximation with CNNs in Sobolev Space: with Applications to Classification. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (NeurIPS, 2022)

Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Joel L. Horowitz; Jian Huang 003 (CoRR, 2022)

Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction. - Wenlu Tang; Guohao Shen; Yuanyuan Lin; Jian Huang 003 (CoRR, 2022)

A Real-time Framework for UAV Indoor Self-Positioning and 3D Mapping Base on 2D Lidar, Stereo Camera and IMU. - Lebin Liang; Haotian Rao; Guohao Shen; Can Wang 002; Xinyu Wu 001 (RCAR, 2023)

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Jian Huang 003 (CoRR, 2023)

Complexity of Feed-Forward Neural Networks from the Perspective of Functional Equivalence. - Guohao Shen (CoRR, 2023)

Wasserstein Generative Regression. - Shanshan Song; Tong Wang; Guohao Shen; Yuanyuan Lin; Jian Huang 003 (CoRR, 2023)

Conditional Stochastic Interpolation for Generative Learning. - Ding Huang; Jian Huang 003; Ting Li; Guohao Shen (CoRR, 2023)

Nonparametric inference on smoothed quantile regression process. - Meiling Hao; Yuanyuan Lin; Guohao Shen; Wen Su (Comput. Stat. Data Anal., 2023)

Exploring the Complexity of Deep Neural Networks through Functional Equivalence. - Guohao Shen (ICML, 2024)

Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. - Guohao Shen; Yuling Jiao; Yuanyuan Lin; Joel L. Horowitz; Jian Huang 003 (J. Mach. Learn. Res., 2024)

Conformal Set-based Human-AI Complementarity with Multiple Experts. - Helbert Paat; Guohao Shen (AAMAS, 2025)

Deep Distributional Learning with Non-crossing Quantile Network. - Guohao Shen; Runpeng Dai; Guojun Wu; Shikai Luo; Chengchun Shi; Hongtu Zhu (CoRR, 2025)

Learning Guarantee of Reward Modeling Using Deep Neural Networks. - Yuanhang Luo; Yeheng Ge; Ruijian Han; Guohao Shen (CoRR, 2025)