activity
20182021
most citedCounterfactual Generation with Knockoffs

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2021

Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals

Wasim Ahmad, Maha Shadaydeh, Joachim Denzler

Estimating causal relations is vital in understanding the complex interactions in multivariate time series. Non-linear coupling of variables is one of the major challenges inaccura…

cs.LG2021

Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning

Violeta Teodora Trifunov, Maha Shadaydeh, Björn Barz +1

There are numerous methods for detecting anomalies in time series, but that is only the first step to understanding them. We strive to exceed this by explaining those anomalies. Th…

cs.CV20213 cited

Counterfactual Generation with Knockoffs

Oana-Iuliana Popescu, Maha Shadaydeh, Joachim Denzler

Human interpretability of deep neural networks' decisions is crucial, especially in domains where these directly affect human lives. Counterfactual explanations of already trained…

cs.CV2020

Analysing the Direction of Emotional Influence in Nonverbal Dyadic Communication: A Facial-Expression Study

Maha Shadaydeh, Lea Mueller, Dana Schneider +3

Identifying the direction of emotional influence in a dyadic dialogue is of increasing interest in the psychological sciences with applications in psychotherapy, analysis of politi…

cs.CV2018

Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality

Lea Müller, Maha Shadaydeh, Martin Thümmel +3

Human nonverbal emotional communication in dyadic dialogs is a process of mutual influence and adaptation. Identifying the direction of influence, or cause-effect relation between…