543 citations · 612 across the 34 of their papers we have counts for
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cs.LG2018★ 543 cited
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy, Lance Kaplan, Melih Kandemir
Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to m…
stat.ML2018★ 16 cited
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haussmann, Fred A. Hamprecht, Melih Kandemir
We propose a new Bayesian Neural Net formulation that affords variational inference for which the evidence lower bound is analytically tractable subject to a tight approximation. W…