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stat.ML2019
Learning Hierarchical Priors in VAEs
Alexej Klushyn, Nutan Chen, Richard Kurle +2
We propose to learn a hierarchical prior in the context of variational autoencoders to avoid the over-regularisation resulting from a standard normal prior distribution. To incenti…
stat.ML2018
Multi-Source Neural Variational Inference
Richard Kurle, Stephan Günnemann, Patrick van der Smagt
Learning from multiple sources of information is an important problem in machine-learning research. The key challenges are learning representations and formulating inference method…