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Explaining Deep Classification of Time-Series Data with Learned Prototypes.

, , , and . KDH@IJCAI, volume 2429 of CEUR Workshop Proceedings, page 15-22. CEUR-WS.org, (2019)

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Bayesian Online Changepoint Detection Of Physiological Transitions., , , and . EMBC, page 45-48. IEEE, (2018)FaiR-N: Fair and Robust Neural Networks for Structured Data., , , and . AIES, page 946-955. ACM, (2021)FASTER-CE: Fast, Sparse, Transparent, and Robust Counterfactual Explanations., , , and . AIAI (4), volume 714 of IFIP Advances in Information and Communication Technology, page 183-196. Springer, (2024)Predicting Bradycardia in Preterm Infants Using Point Process Analysis of Heart Rate., , , and . IEEE Trans. Biomed. Eng., 64 (9): 2300-2308 (2017)Explaining Deep Classification of Time-Series Data with Learned Prototypes., , , and . KDH@IJCAI, volume 2429 of CEUR Workshop Proceedings, page 15-22. CEUR-WS.org, (2019)Automated movement detection reveals features of maturation in preterm infants., , , and . EMBC, page 600-603. IEEE, (2020)Uncovering statistical features of bradycardia severity in premature infants using a point process model., , , and . EMBC, page 5855-5858. IEEE, (2015)Improving heart rate estimation in preterm infants with bivariate point process analysis of heart rate and respiration., , , and . EMBC, page 920-923. IEEE, (2016)Certifai: A Toolkit for Building Trust in AI Systems., , , , , , , , , and 15 other author(s). IJCAI, page 5249-5251. ijcai.org, (2020)Demo.