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Uncertainty Quantification for Large Language Models (LLMs)
Uncertainty Quantification and Deep Learning ǀ Elise Jennings, Argonne National Laboratory
An Introduction to Uncertainty Quantification
Eyke Hüllermeier: Uncertainty Quantification in Machine Learning: From Aleatoric to Epistemic I
Uncertainty Quantification & Machine Learning
2023 5.2 Bayesian Learning and Uncertainty Quantification - Eric Nalisnick
Uncertainty quantification, surrogate building and active learning
Arka Daw - Uncertainty Quantification with Physics-informed Machine Learning
Machine Learning for Uncertainty Quantification: Trusting the Black Box
Uncertainty Quantification in Nuclear Engineering Applications
Uncertainty Quantification in Machine Learning
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Last Updated: September 25, 2026
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Summary
A quick 20 min introduction to various Predictions from modeling and simulation (M&S) are increasingly relied upon to inform critical decision making in a variety of ... This paper takes a fully probabilistic approach by modeling the joint distribution over questions and inputs, defining Presented at the Argonne Training Program on Extreme-Scale Computing 2019. Slides for this presentation are available here: ... Eyke Hüllermeier is a full professor at the Heinz Nicdorf Institute and the Department of Computer Science at Paderborn University ... 2025 ML Academy & Artiste Distinguished Lecture. Okay so now I will talk about the main part of the talk where I will talk about practical methods for As applications in deep learning (DL) continue to seep into critical scientific use-cases, the importance of performing Presenter: James Warner (NASA Langley Research Center) Adopting In this video we dive into a brief overview of In this lecture, we will motivate why the successful application of machine learning models in the real world (in the context of ...