2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights
NeurIPS 2021poster
Bayesian Neural Networks and deep ensembles represent two modern paradigms of uncertainty quantification in deep learning. Yet these approaches struggle to scale mainly due to memory inefficiency, requiring parameter storage several times that of their deterministic counterparts. To address this, we…