Deep Gaussian process models for integrating multifidelity experiments with nonstationary relationships

[1]  A. O'Hagan,et al.  Predicting the output from a complex computer code when fast approximations are available , 2000 .

[2]  Carolyn Conner Seepersad,et al.  Building Surrogate Models Based on Detailed and Approximate , 2004, DAC 2004.

[3]  Tom Dhaene,et al.  Deep Gaussian Process metamodeling of sequentially sampled non-stationary response surfaces , 2017, 2017 Winter Simulation Conference (WSC).

[4]  A. O'Hagan,et al.  Bayesian calibration of computer models , 2001 .

[5]  Neil D. Lawrence,et al.  Bayesian Gaussian Process Latent Variable Model , 2010, AISTATS.

[6]  Neil D. Lawrence,et al.  Deep Gaussian Processes for Multi-fidelity Modeling , 2019, ArXiv.

[7]  Hao Chen,et al.  Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes , 2020, NeurIPS.

[8]  Neil D. Lawrence,et al.  Deep Gaussian Processes , 2012, AISTATS.

[9]  David M. Blei,et al.  Variational Inference: A Review for Statisticians , 2016, ArXiv.

[10]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[11]  Marc Peter Deisenroth,et al.  Doubly Stochastic Variational Inference for Deep Gaussian Processes , 2017, NIPS.

[12]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[13]  Jeong-Soo Park,et al.  A statistical method for tuning a computer code to a data base , 2001 .

[14]  A. Raftery,et al.  Strictly Proper Scoring Rules, Prediction, and Estimation , 2007 .

[15]  Peter Z. G. Qian,et al.  Bayesian Hierarchical Modeling for Integrating Low-Accuracy and High-Accuracy Experiments , 2008, Technometrics.

[16]  Andreas C. Damianou,et al.  Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling , 2017, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  Loïc Brevault,et al.  Bayesian optimization using deep Gaussian processes with applications to aerospace system design , 2021, Optimization and Engineering.

[18]  T. J. Mitchell,et al.  Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer Experiments , 1991 .

[19]  Loic Le Gratiet,et al.  Bayesian Analysis of Hierarchical Multifidelity Codes , 2011, SIAM/ASA J. Uncertain. Quantification.