Li, Didong

12 publications

JMLR 2025 Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data Didong Li, Andrew Jones, Sudipto Banerjee, Barbara E. Engelhardt

AAAI 2025 Contrastive Functional Principal Component Analysis Eric Zhang, Didong Li

JMLR 2025 Deep Generative Models: Complexity, Dimensionality, and Approximation Kevin Wang, Hongqian Niu, Yixin Wang, Didong Li

ICLR 2025 Identifiability for Gaussian Processes with Holomorphic Kernels Ameer Qaqish, Didong Li

TMLR 2025 Lower Ricci Curvature for Efficient Community Detection Yun Jin Park, Didong Li

NeurIPS 2024 Contrastive Dimension Reduction: When and How? Sam Hawke, YueEn Ma, Didong Li

TMLR 2024 KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning Aishwarya Mandyam, Didong Li, Andrew Jones, Diana Cai, Barbara E Engelhardt

NeurIPS 2024 STimage-1K4M: A Histopathology Image-Gene Expression Dataset for Spatial Transcriptomics Jiawen Chen, Muqing Zhou, Wenrong Wu, Jinwei Zhang, Yun Li, Didong Li

JMLR 2024 Spherical Rotation Dimension Reduction with Geometric Loss Functions Hengrui Luo, Jeremy E. Purvis, Didong Li

JMLR 2023 Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds Didong Li, Wenpin Tang, Sudipto Banerjee

NeurIPS 2023 On the Identifiability and Interpretability of Gaussian Process Models Jiawen Chen, Wancen Mu, Yun Li, Didong Li

MLJ 2021 Efficient Weingarten mAP and Curvature Estimation on Manifolds Yueqi Cao, Didong Li, Huafei Sun, Amir H. Assadi, Shiqiang Zhang