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Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity

Apr 10, 2020
Austin Talbot, David Dunson, Kafui Dzirasa, David Carlson

* 23 pages, 6 figures 

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Estimating Uncertainty Intervals from Collaborating Networks

Feb 12, 2020
Tianhui Zhou, Yitong Li, Yuan Wu, David Carlson

* 18 pages, 8 figures 

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Gaussian-Process-Based Dynamic Embedding for Textual Networks

Oct 10, 2019
Pengyu Cheng, Yitong Li, Xinyuan Zhang, Liqun Cheng, David Carlson, Lawrence Carin

* Accepted as NeurIPS 2019 Graph Representation Learning Workshop 

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The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis

Jun 04, 2019
Cynthia Rudin, David Carlson

* INFORMS TutORial 2019 

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StoryGAN: A Sequential Conditional GAN for Story Visualization

Dec 06, 2018
Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David Carlson, Jianfeng Gao


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Stochastic Bouncy Particle Sampler

Jun 14, 2017
Ari Pakman, Dar Gilboa, David Carlson, Liam Paninski

* ICML Camera ready version 

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Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization

Aug 05, 2016
Changyou Chen, David Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin

* Merry Christmas from the Santa (algorithm). AISTATS 2016 

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Partition Functions from Rao-Blackwellized Tempered Sampling

May 25, 2016
David Carlson, Patrick Stinson, Ari Pakman, Liam Paninski

* 15 pages, 8 figures; Appearing at International Conference on Machine Learning 2016 

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Neuroprosthetic decoder training as imitation learning

Mar 14, 2016
Josh Merel, David Carlson, Liam Paninski, John P. Cunningham


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Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks

Dec 23, 2015
Chunyuan Li, Changyou Chen, David Carlson, Lawrence Carin

* AAAI 2016 

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Deep Temporal Sigmoid Belief Networks for Sequence Modeling

Sep 23, 2015
Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

* to appear in NIPS 2015 

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