| The sufficient and necessary condition for the identifiability and estimability of the DINA model Y Gu, G Xu Psychometrika 84, 468-483, 2019 | 81 | 2019 |
| Partial identifiability of restricted latent class models Y Gu, G Xu Annals of Statistics 48 (4), 2082-2107, 2020 | 68 | 2020 |
| Sufficient and Necessary Conditions for the Identifiability of the Q-matrix Y Gu, G Xu Statistica Sinica 31, 449-472, 2021 | 51 | 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 | 34 | 2019 |
| Identifiability of Hierarchical Latent Attribute Models Y Gu, G Xu Statistica Sinica 33 (4), 2561-2591, 2023 | 22* | 2023 |
| Hypothesis testing of the Q-matrix Y Gu, J Liu, G Xu, Z Ying Psychometrika 83 (3), 515-537, 2018 | 15 | 2018 |
| 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 | 13 | 2023 |
| 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 | 12 | 2023 |
| 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 | 7 | 2023 |
| Learning from similar linear representations: adaptivity, minimaxity, and robustness Y Tian, Y Gu, Y Feng arXiv preprint arXiv:2303.17765, 2023 | 6 | 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 | 5 | 2023 |
| A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses L Chen, Y Gu Psychometrika, 2024 | 3 | 2024 |
| Generic Identifiability of the DINA Model and Blessing of Latent Dependence Y Gu Psychometrika 88 (1), 117-131, 2023 | 3 | 2023 |
| Statistical Analysis of Structured Latent Attribute Models Y Gu University of Michigan, 2020 | 1 | 2020 |
| Blessing of Dependence: Identifiability and Geometry of Discrete Models with Multiple Binary Latent Variables Y Gu Bernoulli, 2024 | | 2024 |
| Degree-heterogeneous Latent Class Analysis for High-dimensional Discrete Data Z Lyu, L Chen, Y Gu arXiv preprint arXiv:2402.18745, 2024 | | 2024 |
| New directions in algebraic statistics: Three challenges from 2023 Y Alexandr, M Bakenhus, M Curiel, SK Deshpande, E Gross, Y Gu, M Hill, ... arXiv preprint arXiv:2402.13961, 2024 | | 2024 |
| Latent Conjunctive Bayesian Network: Unify Attribute Hierarchy and Bayesian Network for Cognitive Diagnosis S Lee, Y Gu Annals of Applied Statistics, 2024 | | 2024 |
| New Paradigm of Identifiable General-response Cognitive Diagnostic Models: Beyond Categorical Data S Lee, Y Gu Preprint, 2023 | | 2023 |
| Discussion of "Vintage Factor Analysis with Varimax Performs Statistical Inference" by Rohe & Zeng Y He, Y Gu, Z Ying Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | | 2023 |
