Chen Changyou
Chen Changyou
Assistant Professor at University at Buffalo
Verified email at buffalo.edu - Homepage
TitleCited byYear
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
1402014
Preconditioned stochastic gradient Langevin dynamics for deep neural networks
C Li, C Chen, D Carlson, L Carin
Thirtieth AAAI Conference on Artificial Intelligence, 2016
1002016
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
912015
Low-resolution gait recognition
J Zhang, J Pu, C Chen, R Fleischer
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2010
842010
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
742017
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
572015
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
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
492018
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
452009
Sequential latent Dirichlet allocation
L Du, W Buntine, H Jin, C Chen
Knowledge and information systems 31 (3), 475-503, 2012
442012
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
432016
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
372016
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
312017
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
302015
Learning structured weight uncertainty in bayesian neural networks
S Sun, C Chen, L Carin
Artificial Intelligence and Statistics, 1283-1292, 2017
292017
Supplementary material for dependent normalized random measures
C Chen, V Rao, W Buntine, YW Teh
Proceedings of the International Conference on Machine Learning (ICML), 2013
292013
Dependent hierarchical normalized random measures for dynamic topic modeling
C Chen, N Ding, W Buntine
arXiv preprint arXiv:1206.4671, 2012
282012
Differential topic models
C Chen, W Buntine, N Ding, L Xie, L Du
IEEE transactions on pattern analysis and machine intelligence 37 (2), 230-242, 2014
272014
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
272011
Learning weight uncertainty with stochastic gradient mcmc for shape classification
C Li, A Stevens, C Chen, Y Pu, Z Gan, L Carin
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
252016
Scalable bayesian learning of recurrent neural networks for language modeling
Z Gan, C Li, C Chen, Y Pu, Q Su, L Carin
arXiv preprint arXiv:1611.08034, 2016
242016
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