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Showing 1 to 20 of 54 for “"UQ"”.

  1. Efficient Uncertainty Quantification of Large Language Models

    … finance, and law. Uncertainty Quantification (UQ) is essential for assessing LLM outputs and ensuring trust. However, existing UQ methods for LLMs face challenges: high computational costs, difficulties in handling unstructured outputs, and limited generalizability. This thesis addresses these …

    mit Repository record for Efficient Uncertainty Quantification of Large Language Models (opens in a new tab)

  2. Is the upper quarter Y-Balance test a useful measure to determine upper limb loading response in female competitive gymnasts after upper extremity injury?

    … though the Upper Quarter Y-Balance test (YBT-UQ) may best recreate the sport’s demands. It requires an individual to maintain a plank position while one arm pushes a marker in three directions. The purpose of this project was to explore the YBT-UQ’s test–retest reliability, convergent …

    twu Repository record for Is the upper quarter Y-Balance test a useful measure to determine upper limb loading response in female competitive gymnasts after upper extremity injury? (opens in a new tab)

  3. Uncertainty in the Bifurcation Diagram of a Model of Heart Rhythm Dynamics

    … of these models, uncertainty quantification (UQ) and sensitivity analysis (SA) are important. Polynomial chaos (PC) is a computationally efficient method for UQ and SA in which a model output Y, dependent on some independent uncertain parameters represented by a random vector ξ, is …

    duke Repository record for Uncertainty in the Bifurcation Diagram of a Model of Heart Rhythm Dynamics (opens in a new tab)

  4. Metamodel-based inverse uncertainty quantification of nuclear reactor simulators under the Bayesian framework

    … issue with inverse Uncertainty Quantification (UQ). Inverse UQ is the process to seek statistical descriptions of the random input parameters that are consistent with available high-quality experimental data. We formulate the inverse UQ process under the Bayesian framework using the ``model …

    uiuc Repository record for Metamodel-based inverse uncertainty quantification of nuclear reactor simulators under the Bayesian framework (opens in a new tab)

  5. Assessing the applicability of the ASME V&V20 standard for uncertainty quantification of CFD in nuclear systems fluid modeling

    … nuclear Industry. UncertaInty QuantIfIcatIon (UQ) represents a fundamental area of research necessary to expand the applIcatIon of M&S Into nuclear Industry, but the fIeld Is stIll not mature, and no general consensus exIsts on current UQ methods. In thIs study, the ASME V&V20 I a proposed …

    mit Repository record for Assessing the applicability of the ASME V&V20 standard for uncertainty quantification of CFD in nuclear systems fluid modeling (opens in a new tab)

  6. Stochastic modeling and uncertainty quantification in microelectromechanical systems

    Uncertainty quantification (UQ) has become a necessary step in the design of most modern engineering systems due to the need to create robust devices that can tolerate variations in the manufacturing process or in the operating environment. These variations or uncertainties can be represented by …

    uiuc Repository record for Stochastic modeling and uncertainty quantification in microelectromechanical systems (opens in a new tab)

  7. Deep Gaussian Process Surrogates for Computer Experiments

    … - demand broader uncertainty quantification (UQ). I prioritize UQ through full posterior integration in a Bayesian scheme, hinging on elliptical slice sampling of latent layers. I demonstrate how my DGP's non-stationary flexibility, combined with appropriate UQ, allows for active learning: a …

    vt Repository record for Deep Gaussian Process Surrogates for Computer Experiments (opens in a new tab)

  8. Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification

    … through analysis of uncertainty quantification (UQ) techniques, introduction of novel data sampling strategies, and development of structural similarity analysis algorithm to extract physical insights from diverse data sets. First, we examine the efficacy of UQ for single deterministic neural …

    mit Repository record for Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification (opens in a new tab)

  9. Computational Framework for Uncertainty Quantification, Sensitivity Analysis and Experimental Design of Network-based Computer Simulation Models

    … and prediction, are uncertainty quantification (UQ), sensitivity analysis (SA) and design of experiments (DOE). In addition, network-based computer simulation models, as compared with models based on ordinary and partial differential equations (ODE and PDE), typically involve a significantly …

    vt Repository record for Computational Framework for Uncertainty Quantification, Sensitivity Analysis and Experimental Design of Network-based Computer Simulation Models (opens in a new tab)

  10. Quantum Toroidal Superalgebras

    … isomorphic to the quantum affine superalgebra Uq sl̂(m|n) with parity "s", called vertical and horizontal subalgebras. We show the existence of Miki automorphism of E(s), which exchanges the vertical and horizontal subalgebras. If m and n are different and "s" is standard, we give a …

    iupui Repository record for Quantum Toroidal Superalgebras (opens in a new tab)

  11. High dimensional uncertainty propagation for hypersonic flows and entry propagation

    … a high dimensional uncertainty quantification (UQ) are developed. The first approach performs a single-fidelity non-intrusive forward UQ, while the second one performs a multi fidelity UQ, as an extension of the first approach. Both methods are focused on real engineering problems and, …

    strathclyde Repository record for High dimensional uncertainty propagation for hypersonic flows and entry propagation (opens in a new tab)

  12. Uncertainty quantification in the dynamic analysis of offshore structures

    … use in design. In uncertainty quantification (UQ) for problems dealing with many random or stochastic sources, surrogate models are often developed to reduce costs associated with running a "truth" model to verify response levels associated with low probability. Polynomial chaos expansion (PCE) …

    texas Repository record for Uncertainty quantification in the dynamic analysis of offshore structures (opens in a new tab)

  13. Uncertainty quantification of unconventional reservoirs using assisted history matching methods

    … attractive means for uncertainty quantification (UQ), because they yield an ensemble of qualifying models instead of a single candidate. Here we integrate embedded discrete fracture model (EDFM), one of fractured-reservoirs modeling techniques, with a commercial AHM and optimization tool. We …

    texas Repository record for Uncertainty quantification of unconventional reservoirs using assisted history matching methods (opens in a new tab)

  14. Stochastic Ground Motion Models for Uncertainty Quantification in Earthquake Engineering

    … Quantification in Earthquake Engineering (UQEE). UQEE merges the three components into a consistent probabilistic framework, enabling more informed and reliable decision-making in seismic design and risk management for civil infrastructures. An Uncertainty Quantification (UQ) framework is …

    trento Repository record for Stochastic Ground Motion Models for Uncertainty Quantification in Earthquake Engineering (opens in a new tab)

  15. Inferencing Techniques for Enhanced Monitoring of Thermal-Fluid Systems

    … of sensor data and uncertainty quantification (UQ). We leveraged high-resolution thermal-fluid experiments to demonstrate the solution of two types of IHT problems. The first problem estimates the operating conditions of the experiment based on the minimal use of sensors from high-resolution …

    mit Repository record for Inferencing Techniques for Enhanced Monitoring of Thermal-Fluid Systems (opens in a new tab)

  16. Scalable Surrogates for Counts and Computer Experiments

    … and associated uncertainty quantification (UQ) of the rate at which ENAs are generated is vital to theory development and validation. Gaussian processes (GPs) constitute an excellent nonparametric regression tool that can provide accurate out-of-sample prediction and UQ. But GPs are …

    vt Repository record for Scalable Surrogates for Counts and Computer Experiments (opens in a new tab)

  17. Robust and Data-Driven Uncertainty Quantification Methods as Real-Time Decision Support in Data-Driven Models

    … informed decisions. Uncertainty quantification (UQ) methods are broadly categorized into surrogate-based models, which approximate simulators for speed and efficiency, and probabilistic approaches, such as Bayesian models and Gaussian processes, that inherently capture uncertainty into …

    vt Repository record for Robust and Data-Driven Uncertainty Quantification Methods as Real-Time Decision Support in Data-Driven Models (opens in a new tab)

  18. A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations

    … and computing: Physics, Models, Data, and UQ (Uncertainty Quantification). The framework houses various physical phenomena that occur inside nuclear reactors, such as neutronics, reactor kinetics, fuel depletion, thermal-hydraulics, and fuel performance as well as outside the reactor such …

    uiuc Repository record for A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations (opens in a new tab)

  19. Similarity-Augmented Prediction Methods for Neural Machine Translation

    … probability-based uncertainty quantification (UQ), e.g. Shannon entropy. In this thesis, we study a class of methods which measure semantic similarities between elements in the LM output distribution, which we call similarity-augmented prediction methods. The most well-known instance of this is …

    cambridge Repository record for Similarity-Augmented Prediction Methods for Neural Machine Translation (opens in a new tab)

  20. Hyperconvex hulls in catergories of quasi-metric spaces

    … we shall study tight extensions (called uq-tight extensions in the following) in the categories of T₀-quasi-metric spaces and T₀-ultra-quasimetric spaces. We show in particular that most of the results stay the same as we move from T₀-quasi-metric spaces to T₀-ultra-quasi-metric spaces. …

    cape-town Repository record for Hyperconvex hulls in catergories of quasi-metric spaces (opens in a new tab)

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