Li, Didong
- Inference for Gaussian Processes with Matérn Covariogram on Compact Riemannian Manifolds
2021/04/08 by Li, Didong, Tang, Wenpin, Banerjee, Sudipto · 3 citations
#62G20 #62M30 #FOS: Mathematics #Statistics Theory (math.ST)
- STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics
2024/06/10 by Chen, Jiawen, Zhou, Muqing, Wu, Wenrong +3 · 5 citations
#Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #I.2.10 #I.4.10
- Probabilistic Contrastive Principal Component Analysis
2020/12/14 by Li, Didong, Jones, Andrew, Engelhardt, Barbara · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Methodology (stat.ME)
- The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review
2024/08/24 by Su, Buxin, Zhang, Jiayao, Collina, Natalie +6 · 4 citations
#Applications (stat.AP) #Computer Science and Game Theory (cs.GT) #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Contrastive latent variable modeling with application to case-control sequencing experiments
2021/02/12 by Jones, Andrew, Townes, F. William, Li, Didong +1 · 2 citations
#FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Methodology (stat.ME) #Quantitative Methods (q-bio.QM)
- Efficient Manifold and Subspace Approximations with Spherelets
2017/06/26 by Didong Li, Li, Didong, Minerva Mukhopadhyay +3 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (stat.ML) #Morphological variations and asymmetry #Statistical Methods and Inference
- Exponential-wrapped distributions on symmetric spaces
2020/09/04 by Chevallier, Emmanuel, Didong Li, Yulong Lu +4 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Advanced Statistical Methods and Models #Morphological variations and asymmetry
- From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds
2021/08/17 by Wang, Tianyu, Huang, Yifeng, Li, Didong · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
- Enhancing LLMs with Smart Preprocessing for EHR Analysis
2024/12/03 by Qu, Yixiang, Dai, Yifan, Yu, Shilin +5 · 2 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences
- Kernel Density Bayesian Inverse Reinforcement Learning
2023/03/13 by Mandyam, Aishwarya, Li, Didong, Yao, Jiayu +3 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- On the Identifiability and Interpretability of Gaussian Process Models
2023/10/25 by Chen, Jiawen, Mu, Wancen, Li, Yun +1 · 1 citation
#62M30 #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Spherical Rotation Dimension Reduction with Geometric Loss Functions
2022/04/23 by Luo, Hengrui, Purvis, Jeremy E., Li, Didong · 1 citation
#62R20 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
- Deep Generative Models: Complexity, Dimensionality, and Approximation
2025/04/01 by Xu Wang, Wang, Kevin, Yixin Wang +4 · 2 citations
Computer Science · Physics and Astronomy · #Differential Geometry (math.DG) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
- Contrastive linear regression
2024/01/06 by Zhang, Boyang, Nyquist, Sarah, Jones, Andrew +2 · 1 citation
#FOS: Computer and information sciences #Methodology (stat.ME)