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Feature relevance quantification in explainable AI: A causal problem., , и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 2907-2916. PMLR, (2020)A Theory of Independent Mechanisms for Extrapolation in Generative Models., , , и . AAAI, стр. 6741-6749. AAAI Press, (2021)Über den Zusammenhang zwischen thermodynamisch reversiblem, kryptograpisch seitenkanalfreiem sowie quantenkohärentem Rechnen.. GI Jahrestagung (1), том P-67 из LNI, стр. 443. GI, (2005)Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations., , , и . CLeaR, том 177 из Proceedings of Machine Learning Research, стр. 110-143. PMLR, (2022)Causal Regularization.. NeurIPS, стр. 12683-12693. (2019)Why did the distribution change?, , , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 1666-1674. PMLR, (2021)Testing whether linear equations are causal: A free probability theory approach, , и . CoRR, (2012)The Cause-Effect Problem: Motivation, Ideas, and Popular Misconceptions.. Cause Effect Pairs in Machine Learning, Springer, (2019)Causal structure-based root cause analysis of outliers., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 2357-2369. PMLR, (2022)Self-Compatibility: Evaluating Causal Discovery without Ground Truth., , , , и . AISTATS, том 238 из Proceedings of Machine Learning Research, стр. 4132-4140. PMLR, (2024)