Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DeDUCE: Generating Counterfactual Explanations Efficiently   When an image classifier outputs a wrong class label, it can be helpful to
see what changes in the image would lead to a correct classification. This is
the aim of algorithms generating counterfactual explanations. However, there is
no easily scalable method to generate such counterfactuals. We develop a new
algorithm providing counterfactual explanations for large image classifiers
trained with spectral normalisation at low computational cost. We empirically
compare this algorithm against baselines from the literature; our novel
algorithm consistently finds counterfactuals that are much closer to the
original inputs. At the same time, the realism of these counterfactuals is
comparable to the baselines. The code for all experiments is available at
https://github.com/benedikthoeltgen/DeDUCE.

14
The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg