Bayesian deep learning papers
Below is a list of papers with a Bayesian deep learning flavour.
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
Optional list
Towards Bayesian Deep Learning: A Survey
https://arxiv.org/abs/1604.01662
Deep Gaussian Processes
https://arxiv.org/abs/1211.0358
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