| On Mixing Rates for Bayesian CART J Kim, V Rockova https://arxiv.org/abs/2306.00126, 2023 | 9 | 2023 |
| Sensible adversarial learning J Kim, X Wang | 8 | 2020 |
| Robust sensible adversarial learning of deep neural networks for image classification J Kim, X Wang The Annals of Applied Statistics 17 (2), 961-984, 2023 | 4 | 2023 |
| Deep Bayes Factors J Kim, V Rockova arXiv preprint arXiv:2312.05411, 2023 | 2 | 2023 |
| Deep Generative Quantile Bayes J Kim, PS Zhai, V Ročková arXiv preprint arXiv:2410.08378, 2024 | | 2024 |
| Adaptive Uncertainty Quantification for Generative AI J Kim, S O'Hagan, V Rockova arXiv preprint arXiv:2408.08990, 2024 | | 2024 |
| Inductive Global and Local Manifold Approximation and Projection J Kim, X Wang arXiv preprint arXiv:2406.08097, 2024 | | 2024 |
| Tree Bandits for Generative Bayes S O'Hagan, J Kim, V Rockova arXiv preprint arXiv:2404.10436, 2024 | | 2024 |
| Bridging the gap between human and computer vision in machine learning, adversarial and manifold learning for high-dimensional data J Kim Purdue University Graduate School, 2022 | | 2022 |
Veronika RockovaUniversity of Chicago在 ChicagoBooth.edu 的电子邮件经过验证
Veronika RockovaUniversity of Chicago在 ChicagoBooth.edu 的电子邮件经过验证
Xiao WangProfessor of Statistics, Purdue University在 purdue.edu 的电子邮件经过验证