| Bayesian monotone regression using Gaussian process projection L Lin, DB Dunson Biometrika 101 (2), 303-317, 2014 | 140 | 2014 |
| Dysregulation of prefrontal cortex-mediated slow-evolving limbic dynamics drives stress-induced emotional pathology R Hultman, SD Mague, Q Li, BM Katz, N Michel, L Lin, J Wang, LK David, ... Neuron 91 (2), 439-452, 2016 | 138 | 2016 |
| Scalable and robust Bayesian inference via the median posterior S Minsker, S Srivastava, L Lin, D Dunson International conference on machine learning, 1656-1664, 2014 | 127 | 2014 |
| Robust and scalable Bayes via a median of subset posterior measures S Minsker, S Srivastava, L Lin, DB Dunson Journal of Machine Learning Research 18 (124), 1-40, 2017 | 118 | 2017 |
| Omnibus CLTs for Fréchet means and nonparametric inference on non-Euclidean spaces R Bhattacharya, L Lin Proceedings of the American Mathematical Society 145 (1), 413-428, 2017 | 101 | 2017 |
| Extrinsic local regression on manifold-valued data L Lin, BS Thomas, H Zhu, DB Dunson Journal of the American Statistical Association 112 (519), 1261-1273, 2017 | 84 | 2017 |
| Averages of unlabeled networks: Geometric characterization and asymptotic behavior E Kolaczyk, L Lin, S Rosenberg, J Xu, J Walters Annals of Statistics 48 (1), 514-538, 2020 | 64 | 2020 |
| Optimization of graph neural networks with natural gradient descent MR Izadi, Y Fang, R Stevenson, L Lin 2020 IEEE international conference on big data (big data), 171-179, 2020 | 63 | 2020 |
| Extrinsic Gaussian processes for regression and classification on manifolds L Lin, N Mu, P Cheung, D Dunson Bayesian Analysis 14 (3), 887-906, 2019 | 55 | 2019 |
| On clustering network-valued data SS Mukherjee, P Sarkar, L Lin NIPS’ 17, Proceedings of the 31st International Conference on Neural …, 2017 | 55 | 2017 |
| A course in mathematical statistics and large sample theory R Bhattacharya, L Lin, V Patrangenaru Springer Text in Statistics, Springer, 2016 | 55 | 2016 |
| Intrinsic Gaussian processes on complex constrained domains M Niu, P Cheung, L Lin, Z Dai, N Lawrence, D Dunson Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2019 | 49 | 2019 |
| Change-point detection in dynamic networks via graphon estimation Z Zhao, L Chen, L Lin arXiv preprint arXiv:1908.01823, 2019 | 43 | 2019 |
| Hierarchical stochastic block model for community detection in multiplex networks AA Amini, MS Paez, L Lin Bayesian Analysis 19 (1), 319–345, 2024 | 39 | 2024 |
| Data augmentation for models based on rejection sampling V Rao, L Lin, DB Dunson Biometrika 103 (2), 319-335, 2016 | 36 | 2016 |
| Benchmark dose analysis via nonparametric regression modeling WW Piegorsch, H Xiong, RN Bhattacharya, L Lin Risk Analysis 34 (1), 135-151, 2014 | 31 | 2014 |
| Minimax Posterior Convergence Rates and Model Selection Consistency in High-dimensional DAG Models based on Sparse Cholesky Factors K Lee, J Lee, L Lin Annals of Statistics 47 (No. 6), 3413-3437, 2019 | 30 | 2019 |
| Bayesian nonparametric inference on the Stiefel manifold L Lin, V Rao, DB Dunson Statistics Sinica 27, 535-553, 2017 | 27 | 2017 |
| A likelihood approach to nonparametric estimation of a singular distribution using deep generative models M Chae, D Kim, Y Kim, L Lin Journal of Machine Learning Research 24 (77), 1-42, 2023 | 25 | 2023 |
| Rat intersubjective decisions are encoded by frequency‐specific oscillatory contexts J Schaich Borg, S Srivastava, L Lin, J Heffner, D Dunson, K Dzirasa, ... Brain and behavior 7 (6), e00710, 2017 | 25 | 2017 |
David DunsonArts & Sciences Professor of Statistical Science & MathematicsZweryfikowany adres z duke.edu
