| Preconditioned stochastic gradient Langevin dynamics for deep neural networks C Li, C Chen, D Carlson, L Carin Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 254 | 2016 |
| 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 | 233 | 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 | 221 | 2014 |
| Certified adversarial robustness with additive noise B Li, C Chen, W Wang, L Carin Advances in neural information processing systems 32, 2019 | 189 | 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 | 163 | 2015 |
| Cyclical stochastic gradient MCMC for Bayesian deep learning R Zhang, C Li, J Zhang, C Chen, AG Wilson arXiv preprint arXiv:1902.03932, 2019 | 149 | 2019 |
| 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 | 134 | 2018 |
| Sequential latent Dirichlet allocation L Du, W Buntine, H Jin, C Chen Knowledge and information systems 31 (3), 475-503, 2012 | 117 | 2012 |
| Learning structured weight uncertainty in bayesian neural networks S Sun, C Chen, L Carin Artificial Intelligence and Statistics, 1283-1292, 2017 | 103 | 2017 |
| Low-resolution gait recognition J Zhang, J Pu, C Chen, R Fleischer IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2010 | 99 | 2010 |
| 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 | 94 | 2015 |
| 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 | 93 | 2019 |
| Second-order adversarial attack and certifiable robustness B Li, C Chen, W Wang, L Carin | 87 | 2018 |
| Distributionally adversarial attack T Zheng, C Chen, K Ren Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2253-2260, 2019 | 86 | 2019 |
| Pointcloud saliency maps T Zheng, C Chen, J Yuan, B Li, K Ren Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 84 | 2019 |
| 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 | 81 | 2016 |
| Twitter-network topic model: A full Bayesian treatment for social network and text modeling KW Lim, C Chen, W Buntine arXiv preprint arXiv:1609.06791, 2016 | 70 | 2016 |
| Symmetric variational autoencoder and connections to adversarial learning L Chen, S Dai, Y Pu, E Zhou, C Li, Q Su, C Chen, L Carin International Conference on Artificial Intelligence and Statistics, 661-669, 2018 | 67 | 2018 |
| 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 | 57 | 2019 |
| A unified particle-optimization framework for scalable Bayesian sampling C Chen, R Zhang, W Wang, B Li, L Chen arXiv preprint arXiv:1805.11659, 2018 | 57 | 2018 |
Chunyuan LiMicrosoft Research, RedmondVerified email at microsoft.com
