| Domain adaptive imitation learning K Kim, Y Gu, J Song, S Zhao, S Ermon International Conference on Machine Learning, 5286-5295, 2020 | 107* | 2020 |
| Factor augmented sparse throughput deep relu neural networks for high dimensional regression J Fan, Y Gu Journal of the American Statistical Association 119 (548), 2680-2694, 2024 | 62 | 2024 |
| ZhuSuan: A library for Bayesian deep learning J Shi, J Chen, J Zhu, S Sun, Y Luo, Y Gu, Y Zhou arXiv preprint arXiv:1709.05870, 2017 | 47 | 2017 |
| Language modeling with sparse product of sememe experts Y Gu, J Yan, H Zhu, Z Liu, R Xie, M Sun, F Lin, L Lin Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 40 | 2018 |
| How do noise tails impact on deep ReLU networks? J Fan, Y Gu, WX Zhou The Annals of Statistics 52 (4), 1845-1871, 2024 | 39 | 2024 |
| Convex formulation of overparameterized deep neural networks C Fang, Y Gu, W Zhang, T Zhang IEEE Transactions on Information Theory 68 (8), 5340-5352, 2022 | 34 | 2022 |
| Environment invariant linear least squares J Fan, C Fang, Y Gu, T Zhang The Annals of Statistics 52 (5), 2268-2292, 2024 | 25 | 2024 |
| How to characterize the landscape of overparameterized convolutional neural networks Y Gu, W Zhang, C Fang, JD Lee, T Zhang Advances in Neural Information Processing Systems 33, 3797-3807, 2020 | 15 | 2020 |
| Causality pursuit from heterogeneous environments via neural adversarial invariance learning Y Gu, C Fang, P Bühlmann, J Fan The Annals of Statistics 53 (5), 2230-2257, 2025 | 10 | 2025 |
| Fundamental computational limits in pursuing invariant causal prediction and invariance-guided regularization Y Gu, C Fang, Y Xu, Z Guo, J Fan arXiv preprint arXiv:2501.17354, 2025 | 4 | 2025 |
| Optimal estimation of a factorizable density using diffusion models with ReLU neural networks J Fan, Y Gu, X Li arXiv preprint arXiv:2510.03994, 2025 | 2 | 2025 |
| The implicit bias of heterogeneity towards invariance: A study of multi-environment matrix sensing Y Xu, Y Gu, C Fang Advances in Neural Information Processing Systems 37, 14864-14902, 2024 | 1 | 2024 |
| Near-Optimal Tensor PCA via Normalized Stochastic Gradient Ascent with Overparameterization S Ding, Y Gu, Y Liu, C Fang arXiv preprint arXiv:2510.14329, 2025 | | 2025 |
| CINDES: Classification induced neural density estimator and simulator D Dai, J Fan, Y Gu, D Mukherjee arXiv preprint arXiv:2510.00367, 2025 | | 2025 |
| Algorithmic Statistical Learning and Causality Pursuit Using Neural Networks Y Gu Princeton University, 2025 | | 2025 |
Jianqing FanProfessor of Statistics, Professor of Finance, Princeton UniversityVerified email at princeton.edu
