… We hypothesize that our counterfactual visual explanations … But, given a counterfactual visual
explanation from our … approach to generate counterfactual visual explanations – answering …

… explanations try to shed light on how a model took a specific decision. In contrast, we focus
on the ongrowing branch of counterfactual explanations, … , 63] call themselves counterfactual …

… essential counterfactual feature. We pass the counterfactual feature as a counterfactual
explanation … Figure 1 shows a counterfactual visual explanation between Nashville warbler and …

… satisfactory explanation should be contrastive, counterfactual … Counterfactuals are also
identified that are supported by the … Finally, CLEAR Image measures the fidelity of its explanation …

… In this paper, we overcome the aforementioned challenges and generate our Diffusion Visual
Counterfactual Explanations (DVCEs) for arbitrary ImageNet classifiers (see Fig 1). We use …

… an interactive visual analytics tool, ViCE, that generates counterfactual explanations to …
Interpreting black-box classifiers using instance-level visual explanations. In Proceedings of …

… classifier in order to produce visual explanations. DiVE consists of two … counterfactual loss
LCF that attempts to fool the ML model, a proximity loss Lprox that constrains the explanations …

… To prevent those uninterpretable perturbations, which leave the data manifold by adding
imperceptible high-frequency patterns, counterfactual methods impose that visual explanations …

… on the literature of counterfactual explanations who note five … we will refer to as visual
counterfactual explanations, or VCEs for … Very recently visual counterfactuals based on generative …

… In both cases, the part-attribute information helps disambiguate the visual explanation.
Figure 7 (right) shows a failure case caused by a wrongful prediction from the part-attribute …