- Multifaceted Uncertainty Quantification🔍
- Introduction to Uncertainty Quantification and Industry Challenges🔍
- Uncertainty Quantification in Medicine Science🔍
- Uncertainty Quantification at the Exascale 🔍
- Uncertainty quantification for environmental models🔍
- Uncertainty quantification in drug design🔍
- Uncertainty Quantification🔍
- Introduction to the Uncertainty Quantification Module🔍
Uncertainty Quantification
Multifaceted Uncertainty Quantification - De Gruyter
The book exposes three alternative and competing approaches to uncertainty analysis in engineering. It is composed of some essays on various ...
Introduction to Uncertainty Quantification and Industry Challenges
This webinar introduces stochastic methods and UQ tools, discuss potential implementations in an industry setting, and use case studies.
Uncertainty Quantification in Medicine Science: The Next Big Step
A critical point which has gone largely unnoticed in the medicine field is the need to quantify the predictive limits of the models through uncertainty analysis ...
Uncertainty Quantification at the Exascale (EXA-UQ)
We need to develop uncertainty quantification methodology that allows us to efficiently, and effectively, perform sensitivity and uncertainty calculations with ...
Uncertainty quantification for environmental models
Environmental models are used to evaluate the fate of fertilizers in agricultural settings (including soil denitrification), the degradation of hydrocarbons ...
Uncertainty quantification in drug design - PubMed
Uncertainty quantification will become a key component in autonomous decision making and will be crucial for integrating machine learning and chemistry ...
Uncertainty Quantification - IBM Research
When AI can explain to us that it's unsure, it adds a critical layer of transparency for its safe deployment and use. We're developing ways ...
Introduction to the Uncertainty Quantification Module - COMSOL
Watch this archived presentation for an overview of the Uncertainty Quantification Module, including a quick demo of a steel bracket model.
uncertainty quantification Experts - Staff Directory
Uncertainty Quantification. Expertise in uncertainty quantification. Marcus van Lier-Walqui. Contact Us [email protected] · Disability Services ...
Uncertainty quantification for complex systems - Isaac Newton Institute
The main aim of the programme is to bring applied mathematicians and statisticians together to formulate a common mathematical foundation for UQ and to ...
Comprehensive Uncertainty Quantification and Sensitivity Analysis ...
We demonstrate feasibility of performing comprehensive UQ/SA for cardiac cell models and demonstrate how to assess robustness and overcome model failure.
Uncertainty Quantification for Sparse Deep Learning
We study Gaussian approximability of certain aspects of posterior distributions of sparse deep ReLU architectures in non-parametric regression.
Uncertainty Quantification for Additive Manufacturing Process ...
This article reviews the literature on UQ methodologies focusing on model uncertainty, discusses the corresponding activities of calibration, verification, and ...
Uncertainty Quantification - Vocab, Definition, and Must Know Facts
Uncertainty quantification (UQ) refers to the process of identifying, characterizing, and reducing uncertainty in mathematical models and simulations. This ...
Uncertainty Quantification in Deep Learning - ACM Digital Library
In this tutorial, we present recent advancements in uncertainty quantification for DNNs and their applications across various domains.
Mathematical Science Foundations of Verification Validation and ...
A committee of the National Research Council will examine practices for verification and validation (V&V) and uncertainty quantification (UQ) of large-scale ...
Uncertainty quantification for molecular property predictions with ...
AutoGNNUQ leverages architecture search to generate an ensemble of high-performing GNNs, enabling the estimation of predictive uncertainties.
What is uncertainty quantification? - AI Glossary - DocsBot AI
Uncertainty quantification (UQ) is a field of study that deals with the impact of uncertainty in mathematical modeling and simulation of physical systems. Home.
Uncertainty Quantification for Machine Learning in Engineering ...
This SC will gather contributions presenting state-of-the-art breakthroughs in uncertainty quantification for machine learning.
Uncertainty Quantification with Physics-informed Machine Learning
As applications in deep learning (DL) continue to seep into critical scientific use-cases, the importance of performing uncertainty ...