Vectorization of conjugate-gradient methods for large-scale minimization. - Ionel Michael Navon; Paul Kang-Hoh Phua; M. Ramamurthy (SC, 1988)

A combined simulated annealing and quasi-Newton-like conjugate-gradient method for determining the structure of mixed argon-xenon clusters. - I. M. Navon; F. B. Brown; Daniel H. Robertson (Comput. Chem., 1990)

Numerical Experience with Limited-Memory Quasi-Newton and Truncated Newton Methods. - X. Zou; Ionel Michael Navon; M. Berger; Paul Kang-Hoh Phua; Tamar Schlick; François-Xavier Le Dimet (SIAM J. Optim., 1993)

A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products. - Zhi Wang; I. M. Navon; X. Zou; François-Xavier Le Dimet (Comput. Optim. Appl., 1995)

Performance of efficient minimization algorithms as applied to models of peptides and proteins. - Canan Baysal; Hagai Meirovitch; Ionel Michael Navon (J. Comput. Chem., 1999)

Performance of hybrid methods for large-scale unconstrained optimization as applied to models of proteins. - Bedamati Das; Hagai Meirovitch; Ionel Michael Navon (J. Comput. Chem., 2003)

Numerical and theoretical considerations for sensitivity calculation of discontinuous flow. - Chris Homescu; I. M. Navon (Syst. Control. Lett., 2003)

The Impact of Background Error on Incomplete Observations for 4D-Var Data Assimilation with the FSU GSM. - Ionel Michael Navon; Dacian N. Daescu; Zhuo Liu (International Conference on Computational Science (2), 2005)

A posteriori error estimation by postprocessor independent of method of flowfield calculation. - Aleksey K. Alekseev; I. M. Navon (Comput. Math. Appl., 2006)

Reduced-Order Modeling of the Upper Tropical Pacific Ocean Model using Proper Orthogonal Decomposition. - Yanhua Cao; Jiang Zhu; Zhendong Luo; I. M. Navon (Comput. Math. Appl., 2006)

Open Boundary Control Problem for Navier-Stokes Equations Including a Free Surface: Data Assimilation. - I. Yu. Gejadze; G. J. M. Copeland; I. M. Navon (Comput. Math. Appl., 2006)

Adjoint A Posteriori Error Measures for Anisotropic Mesh Optimisation. - P. W. Power; Christopher C. Pain; M. D. Piggott; Fangxin Fang; Gerard J. Gorman; A. P. Umpleby; Anthony J. H. Goddard; I. M. Navon (Comput. Math. Appl., 2006)

Mixed Finite Element Formulation and Error Estimates Based on Proper Orthogonal Decomposition for the Nonstationary Navier-Stokes Equations. - Zhendong Luo; Jing Chen; I. M. Navon; Xiaozhong Yang (SIAM J. Numer. Anal., 2008)

Comparison of advanced large-scale minimization algorithms for the solution of inverse ill-posed problems. - Aleksey K. Alekseev; I. Michael Navon; Jeff L. Steward (Optim. Methods Softw., 2009)

Application of POD-DEIM Approach for Dimension Reduction of a Diffusive Predator-Prey System with Allee Effect. - Gabriel Dimitriu; Ionel Michael Navon; Razvan Stefanescu (LSSC, 2013)

POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow. - Juan Du 011; Fangxin Fang; Christopher C. Pain; I. M. Navon; Jiang Zhu; David A. Ham (Comput. Math. Appl., 2013)

Reduced order modeling based on POD of a parabolized Navier-Stokes equations model II: Trust region POD 4D VAR data assimilation. - Juan Du 011; I. M. Navon; Jiang Zhu; Fangxin Fang; Aleksey K. Alekseev (Comput. Math. Appl., 2013)

Non-linear Petrov-Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods. - Fangxin Fang; Christopher C. Pain; I. M. Navon; Ahmed H. Elsheikh; Juan Du 011; Dunhui Xiao (J. Comput. Phys., 2013)

POD/DEIM nonlinear model order reduction of an ADI implicit shallow water equations model. - Razvan Stefanescu; Ionel Michael Navon (J. Comput. Phys., 2013)

A reduced-order finite volume element formulation based on POD method and numerical simulation for two-dimensional solute transport problems. - Zhendong Luo; Hong Li 006; Ping Sun; Jing An; Ionel Michael Navon (Math. Comput. Simul., 2013)

Comparison of POD reduced order strategies for the nonlinear 2D Shallow Water Equations. - Razvan Stefanescu; Adrian Sandu; Ionel Michael Navon (CoRR, 2014)

POD/DEIM Strategies for reduced data assimilation systems. - Razvan Stefanescu; Adrian Sandu; Ionel Michael Navon (CoRR, 2014)

Non-linear model reduction for the Navier-Stokes equations using residual DEIM method. - Dunhui Xiao; Fangxin Fang; Andrew G. Buchan; Christopher C. Pain; Ionel Michael Navon; Juan Du 011; G. Hu (J. Comput. Phys., 2014)

A POD reduced order model for resolving angular direction in neutron/photon transport problems. - Andrew G. Buchan; A. A. Calloo; Mark G. Goffin; Steven Dargaville; Fangxin Fang; Christopher C. Pain; Ionel Michael Navon (J. Comput. Phys., 2015)

POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation. - Razvan Stefanescu; Adrian Sandu; Ionel Michael Navon (J. Comput. Phys., 2015)

Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems. - Gabriel Dimitriu; Razvan Stefanescu; Ionel Michael Navon (J. Comput. Appl. Math., 2017)

A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting. - Dunhui Xiao; Pan Yang 014; Fangxin Fang; Jiansheng Xiang; Christopher C. Pain; I. M. Navon; Min Chen (J. Comput. Phys., 2017)

Goal-based sensitivity maps using time windows and ensemble perturbations. - Claire E. Heaney; Pablo Salinas; Fangxin Fang; Christopher C. Pain; I. M. Navon (CoRR, 2018)

Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network. - M. Cheng; Fangxin Fang; Christopher C. Pain; I. M. Navon (CoRR, 2020)

Feasibility of DEIM for retrieving the initial field via dimensionality reduction. - Yuepeng Wang 002; Xuemei Ding; Kun Hu; Fangxin Fang; I. M. Navon; Guang Lin 001 (J. Comput. Phys., 2021)

Sketching Methods for Dynamic Mode Decomposition in Spherical Shallow Water Equations. - Shady E. Ahmed; Omer San; Diana Alina Bistrian; Ionel Michael Navon (CoRR, 2022)

An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes. - Claire E. Heaney; Zef Wolffs; Jón Atli Tómasson; Lyes Kahouadji; Pablo Salinas; André Nicolle; Omar K. Matar; Ionel Michael Navon; Narakorn Srinil; Christopher C. Pain (CoRR, 2022)

A POD reduced-order model based on spectral Galerkin method for solving the space-fractional Gray-Scott model with error estimate. - Mostafa Abbaszadeh; Mehdi Dehghan 002; Ionel Michael Navon (Eng. Comput., 2022)

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis. - S. Ashwin Renganathan; Vishwas Rao; Ionel Michael Navon (J. Comput. Phys., 2023)

Ensemble Kalman filter for GAN-ConvLSTM based long lead-time forecasting. - Meiling Cheng; Fangxin Fang; Ionel Michael Navon; Christopher C. Pain (J. Comput. Sci., 2023)

Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet). - Shengjuan Cai; Fangxin Fang; Vincent-Henri Peuch; Mihai Alexe; Ionel Michael Navon; Yanghua Wang (CoRR, 2024)

Reduced-order modelling based on Koopman operator theory. - Diana Alina Bistrian; Gabriel Dimitriu; Ionel Michael Navon (CoRR, 2024)

A reduced order model discretisation of the space-angle phase-space dimensions of the Boltzmann transport equation with application to nuclear reactor problems. - Andrew G. Buchan; Ionel Michael Navon; Liang Yang (J. Comput. Phys., 2024)

Accelerating inverse inference of ensemble Kalman filter via reduced-order model trained using adaptive sparse observations. - Yuepeng Wang 002; Jie Li; Wenju Zhao; I. M. Navon; Guang Lin 001 (J. Comput. Phys., 2024)