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Better Fiber ODFs from Suboptimal Data with Autoencoder Based Regularization.

, , and . MICCAI (3), volume 11072 of Lecture Notes in Computer Science, page 55-62. Springer, (2018)

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Improving automotive radar spectra object classification using deep learning and multi-class uncertainty calibration. Stuttgart University, Germany, (2022)base-search.net (ftunivstutt:oai:elib.uni-stuttgart.de:11682/12392).Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra., , , , , and . CoRR, (2021)On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration., , , , and . ICPR, page 8029-8036. IEEE, (2020)Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing., , , , and . CoRR, (2021)Validation of composite systems by discrepancy propagation., , , , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 1730-1740. PMLR, (2023)Better Fiber ODFs from Suboptimal Data with Autoencoder Based Regularization., , and . MICCAI (3), volume 11072 of Lecture Notes in Computer Science, page 55-62. Springer, (2018)Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning., , , , and . ICLR, OpenReview.net, (2021)Validation of Composite Systems by Discrepancy Propagation., , , , and . CoRR, (2022)Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning., , , , and . CoRR, (2020)On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration., , , , and . CoRR, (2019)