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Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians., , , and . NeurIPS, page 8836-8846. (2019)Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy Series., , , , and . ECML/PKDD (3), volume 11053 of Lecture Notes in Computer Science, page 325-340. Springer, (2018)Standardizing the Probabilistic Sources of Uncertainty for the sake of Safety Deep Learning., , , , and . SafeAI@AAAI, volume 3381 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Deep Non-crossing Quantiles through the Partial Derivative., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 7902-7914. PMLR, (2022)EUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS., , , , , , , , , and 27 other author(s). ETS, page 1-6. IEEE, (2023)Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models., , and . CoRR, (2024)Aleatoric Uncertainty Modelling in Regression Problems using Deep Learning. University of Barcelona, Spain, (2022)Using Quantile Regression in Neural Networks for Contention Prediction in Multicore Processors., , , , and . ECRTS, volume 231 of LIPIcs, page 4:1-4:25. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)SAFEXPLAIN: Safe and Explainable Critical Embedded Systems Based on AI., , , , , , , , , and 12 other author(s). DATE, page 1-6. IEEE, (2023)Uncertainty Estimation for Black-Box Classification Models: A Use Case for Sentiment Analysis., , , and . IbPRIA (1), volume 11867 of Lecture Notes in Computer Science, page 29-40. Springer, (2019)