David E. Carlson

According to our database1, David E. Carlson authored at least 35 papers between 1980 and 2020.

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Bibliography

2020
Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity.
CoRR, 2020

Estimating Uncertainty Intervals from Collaborating Networks.
CoRR, 2020

Dynamic Embedding on Textual Networks via a Gaussian Process.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Gaussian-Process-Based Dynamic Embedding for Textual Networks.
CoRR, 2019

StoryGAN: A Sequential Conditional GAN for Story Visualization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

On Target Shift in Adversarial Domain Adaptation.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Extracting Relationships by Multi-Domain Matching.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Video Generation From Text.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Targeting EEG/LFP Synchrony with Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

YASS: Yet Another Spike Sorter.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Cross-Spectral Factor Analysis.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Stochastic Bouncy Particle Sampler.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Neuroprosthetic Decoder Training as Imitation Learning.
PLoS Comput. Biol., 2016

Stochastic Spectral Descent for Discrete Graphical Models.
IEEE J. Sel. Top. Signal Process., 2016

Partition Functions from Rao-Blackwellized Tempered Sampling.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
GP Kernels for Cross-Spectrum Analysis.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Temporal Sigmoid Belief Networks for Sequence Modeling.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Preconditioned Spectral Descent for Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalable Deep Poisson Factor Analysis for Topic Modeling.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Learning Deep Sigmoid Belief Networks with Data Augmentation.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Stochastic Spectral Descent for Restricted Boltzmann Machines.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
A Bregman Matrix and the Gradient of Mutual Information for Vector Poisson and Gaussian Channels.
IEEE Trans. Inf. Theory, 2014

Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling.
IEEE Trans. Biomed. Eng., 2014

Analysis of Brain States from Multi-Region LFP Time-Series.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the relations of LFPs & Neural Spike Trains.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Latent Gaussian Models for Topic Modeling.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Designed Measurements for Vector Count Data.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Real-Time Inference for a Gamma Process Model of Neural Spiking.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2011
Detection of Viruses Via Statistical Gene Expression Analysis.
IEEE Trans. Biomed. Eng., 2011

On the Analysis of Multi-Channel Neural Spike Data.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

1980
Bit-Oriented Data Link Control Procedures.
IEEE Trans. Commun., 1980


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