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Dynamics of Inductive ERK Signaling in the Drosophila Embryo

Current biology, 2015-06, Vol.25 (13), p.1784-1790

2015

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Designing networks with resiliency to edge failures using two-stage robust optimization

European journal of operational research, 2019-12, Vol.279 (3), p.704-720

2019

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Manifold learning for parameter reduction

Journal of computational physics, 2019-09, Vol.392, p.419-431

2019

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Nonlinear dimensionality reduction in molecular simulation: The diffusion map approach

Chemical physics letters, 2011-06, Vol.509 (1), p.1-11

2011

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A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

Journal of computational physics, 2017-10, Vol.347, p.290-304

2017

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A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

Journal of computational physics, 2017-09, Vol.344, p.516-533

2017

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External-field-enabled surface nanopattern engineering (a perspective on the article “Current-driven morphological evolution of single-layer epitaxial islands on crystalline substrates” by D. Dasgupta, G. I. Sfyris and D. Maroudas)

Surface science, 2013-12, Vol.618, p.1-2

Kevrekidis, Ioannis G.

2013

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Patch dynamics with buffers for homogenization problems

Journal of computational physics, 2006-03, Vol.213 (1), p.264-287

2006

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Equation-free/Galerkin-free POD-assisted computation of incompressible flows

Journal of computational physics, 2005-08, Vol.207 (2), p.568-587

2005

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The gap-tooth method in particle simulations

Physics letters. A, 2003-09, Vol.316 (3), p.190-195

2003

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A compartmental model for the bicoid gradient

Developmental biology, 2010-09, Vol.345 (1), p.12-17

2010

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Data-driven control of agent-based models: An Equation/Variable-free machine learning approach

Journal of computational physics, 2023-04, Vol.478, p.111953, Article 111953

2023

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RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Journal of computational physics, 2025-01, Vol.520, p.113433, Article 113433

2025

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Telescopic projective methods for parabolic differential equations

Journal of computational physics, 2003-05, Vol.187 (1), p.95-109

2003

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Coarse analysis of collective motion with different communication mechanisms

Mathematical biosciences, 2008-07, Vol.214 (1), p.49-57

2008

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Coarse projective kMC integration: forward/reverse initial and boundary value problems

Journal of computational physics, 2004-05, Vol.196 (2), p.474-489

2004

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AI-Lorenz: A physics-data-driven framework for Black-Box and Gray-Box identification of chaotic systems with symbolic regression

Chaos, solitons and fractals, 2024-11, Vol.188 (C), p.115538, Article 115538

2024

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An equation-free computational approach for extracting population-level behavior from individual-based models of biological dispersal

Physica. D, 2006-03, Vol.215 (1), p.1-24

2006

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Periodically-forced finite networks of heterogeneous globally-coupled oscillators: A low-dimensional approach

Physica. D, 2008-02, Vol.237 (2), p.207-215

2008

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Parsimonious representation of nonlinear dynamical systems through manifold learning: A chemotaxis case study

Applied and computational harmonic analysis, 2018-05, Vol.44 (3), p.759-773

2018

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Coarse-graining the computations of surface reactions: Nonlinear dynamics from atomistic simulators

Surface science, 2009-06, Vol.603 (10), p.1696-1705

2009

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Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

Journal of computational physics, 2023-07, Vol.485, p.112072, Article 112072

2023

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Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

Journal of computational physics, 2024-12, Vol.519, p.113443, Article 113443

2024

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Discrete-time nonlinear feedback linearization via physics-informed machine learning

Journal of computational physics, 2023-11, Vol.492, p.112408, Article 112408

2023

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Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo

Journal of computational physics, 2010-07, Vol.229 (14), p.5299-5314

2010

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Dynamics of Inductive ERK Signaling in the Drosophila Embryo

Designing networks with resiliency to edge failures using two-stage robust optimization

Manifold learning for parameter reduction

Nonlinear dimensionality reduction in molecular simulation: The diffusion map approach

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

External-field-enabled surface nanopattern engineering (a perspective on the article “Current-driven morphological evolution of single-layer epitaxial islands on crystalline substrates” by D. Dasgupta, G. I. Sfyris and D. Maroudas)

Patch dynamics with buffers for homogenization problems

Equation-free/Galerkin-free POD-assisted computation of incompressible flows

The gap-tooth method in particle simulations

A compartmental model for the bicoid gradient

Data-driven control of agent-based models: An Equation/Variable-free machine learning approach

RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Telescopic projective methods for parabolic differential equations

Coarse analysis of collective motion with different communication mechanisms

Coarse projective kMC integration: forward/reverse initial and boundary value problems

AI-Lorenz: A physics-data-driven framework for Black-Box and Gray-Box identification of chaotic systems with symbolic regression

An equation-free computational approach for extracting population-level behavior from individual-based models of biological dispersal

Periodically-forced finite networks of heterogeneous globally-coupled oscillators: A low-dimensional approach

Parsimonious representation of nonlinear dynamical systems through manifold learning: A chemotaxis case study

Coarse-graining the computations of surface reactions: Nonlinear dynamics from atomistic simulators

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

Discrete-time nonlinear feedback linearization via physics-informed machine learning

Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo

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