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Tracking Multiple Objects with Multimodal Dependent Measurements: Bayesian Nonparametric Modeling.

, , , and . ACSSC, page 1847-1851. IEEE, (2019)

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Tracking Multiple Objects with Multimodal Dependent Measurements: Bayesian Nonparametric Modeling., , , and . ACSSC, page 1847-1851. IEEE, (2019)Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning., and . CoRR, (2019)Learn-By-Calibrating: Using Calibration As A Training Objective., , and . ICASSP, page 3632-3636. IEEE, (2020)Improving Reliability of Clinical Models Using Prediction Calibration., , , and . UNSURE/GRAIL@MICCAI, volume 12443 of Lecture Notes in Computer Science, page 71-80. Springer, (2020)Learn-By-Calibrating: Using Calibration as a Training Objective., , and . CoRR, (2019)Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration., , , and . CoRR, (2020)Use of Hierarchical Dirichlet Processes to Integrate Dependent Observations From Multiple Disparate Sensors for Tracking., , , and . FUSION, page 1-7. IEEE, (2019)Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models., , , and . CoRR, (2020)Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification., and . CoRR, (2020)Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors., , , and . CoRR, (2019)