Preconditioned stochastic gradient Langevin dynamics for deep neural networks C Li, C Chen, D Carlson, L Carin Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 380 | 2016 |
Certified adversarial robustness with additive noise B Li, C Chen, W Wang, L Carin Advances in neural information processing systems 32, 2019 | 357 | 2019 |
Cyclical stochastic gradient MCMC for Bayesian deep learning R Zhang, C Li, J Zhang, C Chen, AG Wilson arXiv preprint arXiv:1902.03932, 2019 | 298 | 2019 |
Alice: Towards understanding adversarial learning for joint distribution matching C Li, H Liu, C Chen, Y Pu, L Chen, R Henao, L Carin Advances in neural information processing systems 30, 2017 | 276 | 2017 |
Bayesian sampling using stochastic gradient thermostats N Ding, Y Fang, R Babbush, C Chen, RD Skeel, H Neven Advances in neural information processing systems 27, 2014 | 268 | 2014 |
Towards language-free training for text-to-image generation Y Zhou, R Zhang, C Chen, C Li, C Tensmeyer, T Yu, J Gu, J Xu, T Sun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 213 | 2022 |
Pointcloud saliency maps T Zheng, C Chen, J Yuan, B Li, K Ren Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 205 | 2019 |
On the convergence of stochastic gradient MCMC algorithms with high-order integrators C Chen, N Ding, L Carin Advances in neural information processing systems 28, 2015 | 199 | 2015 |
Zero-shot learning via class-conditioned deep generative models W Wang, Y Pu, V Verma, K Fan, Y Zhang, C Chen, P Rai, L Carin Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 171 | 2018 |
Topic-guided variational autoencoders for text generation W Wang, Z Gan, H Xu, R Zhang, G Wang, D Shen, C Chen, L Carin arXiv preprint arXiv:1903.07137, 2019 | 148 | 2019 |
Distributionally adversarial attack T Zheng, C Chen, K Ren Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2253-2260, 2019 | 141 | 2019 |
Learning structured weight uncertainty in bayesian neural networks S Sun, C Chen, L Carin Artificial Intelligence and Statistics, 1283-1292, 2017 | 137 | 2017 |
Sequential latent Dirichlet allocation L Du, W Buntine, H Jin, C Chen Knowledge and information systems 31, 475-503, 2012 | 129 | 2012 |
Scalable deep Poisson factor analysis for topic modeling Z Gan, C Chen, R Henao, D Carlson, L Carin International Conference on Machine Learning, 1823-1832, 2015 | 107 | 2015 |
Low-resolution gait recognition J Zhang, J Pu, C Chen, R Fleischer IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2010 | 106 | 2010 |
Bridging the gap between stochastic gradient MCMC and stochastic optimization C Chen, D Carlson, Z Gan, C Li, L Carin Artificial Intelligence and Statistics, 1051-1060, 2016 | 103 | 2016 |
Second-order adversarial attack and certifiable robustness B Li, C Chen, W Wang, L Carin | 100 | 2018 |
Holistic brain tumor screening and classification based on densenet and recurrent neural network Y Zhou, Z Li, H Zhu, C Chen, M Gao, K Xu, J Xu Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 96 | 2019 |
Improving sequence-to-sequence learning via optimal transport L Chen, Y Zhang, R Zhang, C Tao, Z Gan, H Zhang, B Li, D Shen, C Chen, ... arXiv preprint arXiv:1901.06283, 2019 | 94 | 2019 |
Towards fair federated learning with zero-shot data augmentation W Hao, M El-Khamy, J Lee, J Zhang, KJ Liang, C Chen, LC Duke Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 85 | 2021 |