Bayesian deep learning - Deep Bayesian learning papers

Below is a list of papers with Bayesian deep learning - Deep Bayesian learning flavour.

Thanks to Hongliang for the references.

Preferred list

Gaussian Process Behaviour in Wide Deep Neural Networks

https://openreview.net/forum?id=H1-nGgWC-

Bayesian Conditional Generative Adverserial Networks

https://arxiv.org/abs/1706.05477

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks

https://arxiv.org/abs/1701.04722

Stick-Breaking Variational Autoencoders

https://arxiv.org/abs/1605.06197

A Bayesian encourages dropout

https://arxiv.org/abs/1412.7003

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

https://arxiv.org/abs/1506.02142

Bayesian GAN

https://arxiv.org/abs/1705.09558

Deep Learning: A Bayesian Perspective

https://arxiv.org/abs/1706.00473

Towards Bayesian Deep Learning: A Survey

https://arxiv.org/abs/1604.01662

Optional list

Deep Gaussian Processes

https://arxiv.org/abs/1211.0358

Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks

https://papers.nips.cc/paper/6827-deep-multi-task-gaussian-processes-for-survival-analysis-with-competing-risks

A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis

https://arxiv.org/abs/1411.4423

Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

https://arxiv.org/abs/1611.02648

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://arxiv.org/abs/1511.02680

Nonparametric Variational Auto-encoders for Hierarchical Representation Learning

https://arxiv.org/abs/1703.07027

Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering

https://arxiv.org/abs/1611.05148

Variational Dropout and the Local Reparameterization Trick

https://arxiv.org/abs/1506.02557