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GALE: Globally Assessing Local Explanations.

, , , , , and . TAG-ML, volume 196 of Proceedings of Machine Learning Research, page 322-331. PMLR, (2022)

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Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations., , , , and . CoRR, (2020)Topological Representations of Local Explanations., , , , , and . CoRR, (2022)Calibrate: Interactive Analysis of Probabilistic Model Output., , , , and . CoRR, (2022)BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence., , , , , , , and . CoRR, (2022)An Interpretable Deep Classifier for Counterfactual Generation., , and . ICAIF, page 36-43. ACM, (2022)SUBPLEX: Towards a Better Understanding of Black Box Model Explanations at the Subpopulation Level., , , , , , , and . CoRR, (2020)Counterfactual Explanations via Latent Space Projection and Interpolation., , , and . CoRR, (2021)SUBPLEX: A Visual Analytics Approach to Understand Local Model Explanations at the Subpopulation Level., , , , , , , and . IEEE Computer Graphics and Applications, 42 (6): 24-36 (2022)Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation., , , and . IEEE BigData, page 1809-1816. IEEE, (2021)Understanding Counterfactual Generation using Maximum Mean Discrepancy., , and . ICAIF, page 44-52. ACM, (2022)