# Mathias Berglund

According to our database

Collaborative distances:

^{1}, Mathias Berglund authored at least 14 papers between 2013 and 2017.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2017

Unsupervised Networks, Stochasticity and Optimization in Deep Learning.

PhD thesis, 2017

2016

Tagger: Deep Unsupervised Perceptual Grouping.

CoRR, 2016

Tagger: Deep Unsupervised Perceptual Grouping.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters.

Proceedings of the 33nd International Conference on Machine Learning, 2016

Stochastic gradient estimate variance in contrastive divergence and persistent contrastive divergence.

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Measuring the usefulness of hidden units in Boltzmann machines with mutual information.

Neural Networks, 2015

Semi-Supervised Learning with Ladder Network.

CoRR, 2015

Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters.

CoRR, 2015

Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series.

CoRR, 2015

Semi-supervised Learning with Ladder Networks.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bidirectional Recurrent Neural Networks as Generative Models.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Techniques for Learning Binary Stochastic Feedforward Neural Networks.

CoRR, 2014

2013

Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence.

CoRR, 2013

Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information.

Proceedings of the Neural Information Processing - 20th International Conference, 2013