Quality of Uncertainty Quantification for Bayesian Neural Network Inference
Yao, Jiayu, Pan, Weiwei, Ghosh, Soumya, Doshi-Velez, Finale
Bayesian Neural Networks (BNNs) place priors There exists a large body of work to improve the quality of over the parameters in a neural network. Inference inference for Bayesian neural networks (BNNs) by improving in BNNs, however, is difficult; all inference the approximate inference procedure (e.g. Graves 2011; methods for BNNs are approximate. In this work, Blundell et al. 2015; Hernández-Lobato et al. 2016, to name we empirically compare the quality of predictive a few), or by improving the flexibility of the variational uncertainty estimates for 10 common inference approximation for variational inference (e.g.
Jun-23-2019
- Country:
- Europe > Netherlands
- North Holland > Amsterdam (0.04)
- North America > United States
- Massachusetts > Middlesex County > Cambridge (0.04)
- Europe > Netherlands
- Genre:
- Research Report (1.00)
- Technology: