| Bayesian sampling using stochastic gradient thermostats N Ding, Y Fang, R Babbush, C Chen, RD Skeel, H Neven Advances in neural information processing systems, 3203-3211, 2014 | 177 | 2014 |
| Preconditioned stochastic gradient Langevin dynamics for deep neural networks C Li, C Chen, D Carlson, L Carin arXiv preprint arXiv:1512.07666, 2015 | 158 | 2015 |
| 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, 5495-5503, 2017 | 147 | 2017 |
| On the convergence of stochastic gradient MCMC algorithms with high-order integrators C Chen, N Ding, L Carin Advances in Neural Information Processing Systems, 2278-2286, 2015 | 127 | 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 | 94 | 2010 |
| Zero-shot learning via class-conditioned deep generative models W Wang, Y Pu, VK Verma, K Fan, Y Zhang, C Chen, P Rai, L Carin arXiv preprint arXiv:1711.05820, 2017 | 85 | 2017 |
| 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 | 69 | 2015 |
| Learning structured weight uncertainty in bayesian neural networks S Sun, C Chen, L Carin Artificial Intelligence and Statistics, 1283-1292, 2017 | 63 | 2017 |
| Adversarial symmetric variational autoencoder Y Pu, W Wang, R Henao, L Chen, Z Gan, C Li, L Carin Advances in neural information processing systems, 4330-4339, 2017 | 58 | 2017 |
| 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 | 58 | 2016 |
| Adversarial text generation via feature-mover's distance L Chen, S Dai, C Tao, H Zhang, Z Gan, D Shen, Y Zhang, G Wang, ... Advances in Neural Information Processing Systems, 4666-4677, 2018 | 54 | 2018 |
| Second-order adversarial attack and certifiable robustness B Li, C Chen, W Wang, L Carin | 52 | 2018 |
| 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 | 52 | 2016 |
| Distance approximating dimension reduction of Riemannian manifolds C Chen, J Zhang, R Fleischer IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2009 | 49 | 2009 |
| Sequential latent Dirichlet allocation L Du, W Buntine, H Jin, C Chen Knowledge and information systems 31 (3), 475-503, 2012 | 48 | 2012 |
| 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 | 43 | 2019 |
| Certified adversarial robustness with additive noise B Li, C Chen, W Wang, L Carin Advances in Neural Information Processing Systems, 9464-9474, 2019 | 39 | 2019 |
| Sampling table configurations for the hierarchical Poisson-Dirichlet process C Chen, L Du, W Buntine Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 38 | 2011 |
| Distributionally adversarial attack T Zheng, C Chen, K Ren Proceedings of the AAAI Conference on Artificial Intelligence 33, 2253-2260, 2019 | 37 | 2019 |
| Scalable bayesian non-negative tensor factorization for massive count data C Hu, P Rai, C Chen, M Harding, L Carin Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015 | 37 | 2015 |
Lawrence CarinProfessor of Electrical and Computer Engineering, Duke UniversityVerified email at ece.duke.edu
