Bayesian Convolutional Neural Networks

By Felix Laumann, Kumar Shridhar, Adrian Llopart Maurin. 2018

23 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Willem Waegeman
2. Eyke Hüllermeier
3. Min-Ling Zhang
4. Mohammad S. Sorower
5. Francisco Charte
6. Krzysztof Dembczynski
7. Jesse Read
8. Weiwei Cheng

Citations in the corpus

• Aleatoric and Epistemic Uncertainty in Machine Learning: A Tutorial Introduction (2019, background): “An important example is Dropout variational inference (Gal and Ghahramani, 2016), which establishes an interesting connection between (variational) Bayesian inference and the idea of using Dropout as a learning technique for neural networks.”