A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications | Paper Citation Record

Observation a58dfc93-7da8-4e66-bf18-2ef44c857691 · outbound

This paper cites Reengi- neering aircraft structural life prediction using a digital twin.International Journal of Aerospace Engineering, 2011(1):154798, 2011.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Reengi- neering aircraft structural life prediction using a digital twin.International Journal of Aerospace Engineering, 2011(1):154798, 2011

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This paper cites The digital twin paradigm for future nasa and us air force vehicles.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications The digital twin paradigm for future nasa and us air force vehicles

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This paper cites Grieves.Digital Twins: Past, Present, and Future, pages 97–121.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Grieves.Digital Twins: Past, Present, and Future, pages 97–121

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This paper cites Data-driven physics-based digital twins via a library of component-based reduced-order models.International Journal for Numerical Methods in Engineering, 123(13):2986–3003, 2022.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Data-driven physics-based digital twins via a library of component-based reduced-order models.International Journal for Numerical Methods in Engineering, 123(13):2986–3003, 2022

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This paper cites On the effects of modeling as-manufactured geometry: Toward digital twin.International Journal of Aerospace Engineering, 2014(1):439278, 2014.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications On the effects of modeling as-manufactured geometry: Toward digital twin.International Journal of Aerospace Engineering, 2014(1):439278, 2014

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Unresolved cited work

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This paper cites Advisory Circular 25.571-1D: Damage Tolerance and Fatigue Evaluation of Structure.https://www.faa.gov/documentLibrary/media/ Advisory_Circular/AC_25_571-1D_.pdf, 2011.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Advisory Circular 25.571-1D: Damage Tolerance and Fatigue Evaluation of Structure.https://www.faa.gov/documentLibrary/media/ Advisory_Circular/AC_25_571-1D_.pdf, 2011

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This paper cites Airframe digital twin technology adaptability assessment and technology demonstration.Engineering Fracture Mechan- ics, 225:106793, 2020.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Airframe digital twin technology adaptability assessment and technology demonstration.Engineering Fracture Mechan- ics, 225:106793, 2020

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This paper cites Probabilistic methods for risk assess- ment of airframe digital twin structures.Engineering Fracture Mechanics, 221:106674,.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Probabilistic methods for risk assess- ment of airframe digital twin structures.Engineering Fracture Mechanics, 221:106674,

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications McDowell

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Observation 1ce5339a-d2c6-4765-a1f7-7d5bb2df021a · outbound

This paper cites Yeratapally, Patrick E.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Yeratapally, Patrick E

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This paper cites doi: https://doi.org/10.1016/j.engfracmech.2019.106673.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications doi: https://doi.org/10.1016/j.engfracmech.2019.106673

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This paper cites Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes

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This paper cites Solving High Frequency and Multi-Scale PDEs with Gaussian Processes.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

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Observation 73a6d0d2-d8cb-4517-b542-de60bda47aeb · outbound

This paper cites Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature

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This paper cites Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression

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This paper cites Derivative Observations in Gaussian Process Models of Dynamic Systems.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Derivative Observations in Gaussian Process Models of Dynamic Systems

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This paper cites Scaling Gaussian Processes with Derivative Information Using Variational Inference.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Scaling Gaussian Processes with Derivative Information Using Variational Inference

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This paper cites DGP-LVM: Derivative Gaussian process latent variable models.Statistics and Computing, 35(5):120, October.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications DGP-LVM: Derivative Gaussian process latent variable models.Statistics and Computing, 35(5):120, October

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Observation 9266dca5-1f73-422e-8bb9-16ca047bf1bd · outbound

This paper cites Scaling Gaussian Process Regression with Derivatives.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Scaling Gaussian Process Regression with Derivatives

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This paper cites Hoerl and Robert W.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Hoerl and Robert W

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This paper cites Critical current of a Josephson junction containing a conical magnet.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Critical current of a Josephson junction containing a conical magnet

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Observation 1241e163-b2c1-463c-9f64-11f2f6702fa8 · outbound

This paper cites When Gaussian Process Meets Big Data: A Review of Scalable GPs.IEEE Transactions on Neural Networks and Learning Systems, 31(11):4405–4423, November 2020.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications When Gaussian Process Meets Big Data: A Review of Scalable GPs.IEEE Transactions on Neural Networks and Learning Systems, 31(11):4405–4423, November 2020

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This paper cites Hida-matérn kernel hida-matérn kernel.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Hida-matérn kernel hida-matérn kernel

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Recursive Sampling for the Nystr\"om Method

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This paper cites Epperly, Joel A.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Epperly, Joel A

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Unresolved cited work

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This paper cites Heaton, Abhirup Datta, Andrew O.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Heaton, Abhirup Datta, Andrew O

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This paper cites Finley, and Alan E.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Finley, and Alan E

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This paper cites Finley, Nicholas A.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Finley, Nicholas A

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Sparse greedy gaussian process regression

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Covariance Tapering for Interpolation of Large Spatial Datasets.Journal of Computational and Graphical Statistics, 15(3):502–523, September 2006

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Random Features for Large-Scale Kernel Machines

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications A unifying view of sparse ap- proximate gaussian process regression.Journal of Machine Learning Research, 6(65): 1939–1959, 2005

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Stein, Zhiyi Chi, and Leah J

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Scaled Vecchia approximation for fast computer-model emulation

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Sparse inverse Cholesky factorization of dense kernel matrices by greedy conditional selection

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Permutation and Grouping Methods for Sharpening Gaussian Process Approximations.Technometrics, 60(4):415–429, October 2018

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Unresolved cited work

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications A General Framework for Vec- chia Approximations of Gaussian Processes.Statistical Science, 36(1), Febru- ary 2021

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Sparse Cholesky Factorization by Kullback–Leibler Minimization.SIAM Journal on Scientific Computing, 43(3):A2019– A2046, January 2021

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This paper cites Solving and Learning Nonlinear PDEs with Gaussian Processes.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Solving and Learning Nonlinear PDEs with Gaussian Processes

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Observation d1b90ec7-63f9-434d-8757-7992ac54e471 · outbound

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference

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Observation d9daadf9-b559-4331-ac3a-78fb61504ac4 · outbound

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Davis and William W

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Leser, James E

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Computational fracture mechanics.Encyclopedia of computational mechanics, 2004

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Unresolved cited work

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Unresolved cited work

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications point-wise ordering algorithm 2

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications Kirby, and Jacob Hochhalter

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Observation 2c95e0a7-f693-485d-a4b2-6180c60a02a3 · outbound

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications point-wise ordering algorithm 2

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A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications DGP-LVM: Derivative Gaussian process latent variable models

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Observation f77bbd50-6a04-463d-b8c3-72dcfb5d8934 · outbound

This paper cites URLhttp://arxiv.org/abs/1609.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications URLhttp://arxiv.org/abs/1609

Reference 2723

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Observation dfb89a30-13ec-41ab-a760-61a6e105d7ce · outbound

This paper cites URLhttps://www.

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications URLhttps://www

Reference 7944

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