| The sufficient and necessary condition for the identifiability and estimability of the DINA model Y Gu, G Xu Psychometrika 84, 468-483, 2019 | 97 | 2019 |
| Partial identifiability of restricted latent class models Y Gu, G Xu Annals of Statistics 48 (4), 2082-2107, 2020 | 73 | 2020 |
| Sufficient and Necessary Conditions for the Identifiability of the Q-matrix Y Gu, G Xu Statistica Sinica 31, 449-472, 2021 | 65 | 2021 |
| Learning attribute patterns in high-dimensional structured latent attribute models Y Gu, G Xu Journal of Machine Learning Research 20 (115), 1-58, 2019 | 35 | 2019 |
| Bayesian Pyramids: Identifiable Multilayer Discrete Latent Structure Models for Discrete Data Y Gu, DB Dunson Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 24 | 2023 |
| Identifiability of Hierarchical Latent Attribute Models Y Gu, G Xu Statistica Sinica 33 (4), 2561-2591, 2023 | 23* | 2023 |
| Learning from similar linear representations: Adaptivity, minimaxity, and robustness Y Tian, Y Gu, Y Feng arXiv preprint arXiv:2303.17765, 2023 | 19 | 2023 |
| A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis Y Gu, G Xu Journal of the American Statistical Association 118 (541), 746-760, 2023 | 16 | 2023 |
| Hypothesis testing of the Q-matrix Y Gu, J Liu, G Xu, Z Ying Psychometrika 83 (3), 515-537, 2018 | 16 | 2018 |
| A tensor-EM method for large-scale latent class analysis with binary responses Z Zeng, Y Gu, G Xu Psychometrika 88 (2), 580-612, 2023 | 14 | 2023 |
| Dimension-grouped mixed membership models for multivariate categorical data Y Gu, EA Erosheva, G Xu, DB Dunson Journal of Machine Learning Research 24 (88), 1-49, 2023 | 11 | 2023 |
| A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses L Chen, Y Gu Psychometrika 89 (2), 626-657, 2024 | 9 | 2024 |
| New Paradigm of Identifiable General-response Cognitive Diagnostic Models: Beyond Categorical Data S Lee, Y Gu Psychometrika 89 (4), 1304-1336, 2024 | 6 | 2024 |
| Generic Identifiability of the DINA Model and Blessing of Latent Dependence Y Gu Psychometrika 88 (1), 117-131, 2023 | 4 | 2023 |
| Blessing of dependence: Identifiability and geometry of discrete models with multiple binary latent variables Y Gu Bernoulli 31 (2), 948-972, 2025 | 3 | 2025 |
| Degree-heterogeneous Latent Class Analysis for High-dimensional Discrete Data Z Lyu, L Chen, Y Gu Journal of the American Statistical Association, 1-25, 2025 | 3 | 2025 |
| Going Deep in Diagnostic Modeling: Deep Cognitive Diagnostic Models (DeepCDMs) Y Gu Psychometrika 89 (1), 118–150, 2024 | 3 | 2024 |
| Generalized grade-of-membership estimation for high-dimensional locally dependent data L Chen, C Huang, Y Gu arXiv preprint arXiv:2412.19796, 2024 | 1 | 2024 |
| A Blockwise Mixed Membership Model for Multivariate Longitudinal Data: Discovering Clinical Heterogeneity and Identifying Parkinson's Disease Subtypes K Kang, Y Gu arXiv preprint arXiv:2410.01235, 2024 | 1 | 2024 |
| Bayesian Deep Generative Models for Multiplex Networks with Multiscale Overlapping Clusters Y Zhou, Y Gu, DB Dunson arXiv preprint arXiv:2405.20936, 2024 | 1* | 2024 |