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Martin Kukla

1 accepted papers

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…

Cited by 22SourcePDFScholar