Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Masksembles for Uncertainty Estimation   Deep neural networks have amply demonstrated their prowess but estimating the
reliability of their predictions remains challenging. Deep Ensembles are widely
considered as being one of the best methods for generating uncertainty
estimates but are very expensive to train and evaluate. MC-Dropout is another
popular alternative, which is less expensive, but also less reliable. Our
central intuition is that there is a continuous spectrum of ensemble-like
models of which MC-Dropout and Deep Ensembles are extreme examples. The first
uses an effectively infinite number of highly correlated models while the
second relies on a finite number of independent models.
  To combine the benefits of both, we introduce Masksembles. Instead of
randomly dropping parts of the network as in MC-dropout, Masksemble relies on a
fixed number of binary masks, which are parameterized in a way that allows to
change correlations between individual models. Namely, by controlling the
overlap between the masks and their density one can choose the optimal
configuration for the task at hand. This leads to a simple and easy to
implement method with performance on par with Ensembles at a fraction of the
cost. We experimentally validate Masksembles on two widely used datasets,
CIFAR10 and ImageNet.

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The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
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The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
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The categories of this paper are: nlin
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The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
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The categories of this paper are: astro-ph