Deep Learning Software

  

Z. Gan, R. Henao, D. Carlson and L. Carin, Learning Deep Sigmoid Belief Networks with Data Augmentation, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2015, Software

 

Z. Gan, C. Chen, R. Henao, D. Carlson and L. Carin, Scalable Deep Poisson Factor Analysis for Topic Modeling, Supplementary Material, Int. Conf. Machine Learning (ICML), 2015, Software

 

Z. Gan, C. Li, R. Henao, D. Carlson and L. Carin, Deep Temporal Sigmoid Belief Networks for Sequence Modeling, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015, Software

 

C. Chen, N. Ding and L. Carin, On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators, Neural and Information Processing Systems (NIPS), 2015, Software

 

 

 

C. Chen, D. Carlson, Z. Gan, C. Li and L. Carin, Bridging the Gap Between Stochastic Gradient MCMC and Stochastic Optimization, Artificial Intelligence and Statistics (AISTATS), 2016, Software

 

 

 

C. Li, C. Chen, D. Carlson and L. Carin, Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks, Proc. American Association of Artificial Intelligence (AAAI), 2016, Software

 

 

 

C. Li, C. Chen, K. Fan and L. Carin, High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models, Proc. American Association of Artificial Intelligence (AAAI), 2016, Software

 

 

 

C. Chen, N. Ding, C. Li, Y. Zhang, and L. Carin, Stochastic Gradient MCMC with Stale Gradients, Supplementary Material, Neural and Information Processing Systems (NIPS), 2016, Software

 

 

 

Z. Gan, C. Li, C. Chen, Y. Pu, Q. Su, and L. Carin, Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling, Association for Computational Linguistics (ACL), 2017, Software