… point as anomalous, we can look only at the feature f 1 for all the … attribute f 1 vary between
− 1 and 8 , it takes the value 12 . … 5, when trying to explain the abnormality of the square data …

… how are we to tell whether the existence of an anomaly is in fact a problem for a theory? The
… one, if it will be greater at all. When we expect an anomaly given T , the fact that we find one …

… In general, obtaining outlier explanations that can explain the inner workings of each anomaly
… In our work, we focus on developing methods that can explain detected outliers one at a …

… Despite that, there are only a few anomaly detection methods trying to explain … them to
anomaly detection problems by selecting one or multiple classes and labelling them as anomalies …

… the most important anomalies and may increase their trust in … that uses Kernel SHAP to
explain anomalies detected by an … combination X 1 = X 5 − X 2 , we expect that X 1 will have a …

… One of the puzzling aspects of the present anomalies is that … coefficients of these operators
to all the relevant semi-leptonic … simultaneously explain both anomalies while satisfying all …

… ) of the overall system are composed of the following two types of true anomalies: 1) anomalies
… We consider anomaly detection problems defined over a set of N data points {x1,...,xN }, …

… anomalies correspond to BRST cohomologies at ghost number one. We discuss why and
how … We will only talk about anomalies defined in this way. They are referred to as consistent …

… to the view I defended in §1, we interpret quantified statements by restricting their
domains to avoid having to interpret them in ways that would prevent them from being truth-evaluable. …

… We define an anomaly as redundancy or inconsistency caused by the evolution of a feature
model… Among all explanations, we present the improved one concerning length and coloring. …