Ioannis G. Kevrekidis
Orcid: 0000-0003-2220-3522Affiliations:
- Johns Hopkins University, Chemical and Biomolecular Engineering, Baltimore, MD, USA
- Princeton University, Department of Chemical Engineering
According to our database1,
Ioannis G. Kevrekidis
authored at least 168 papers
between 1993 and 2025.
Collaborative distances:
Collaborative distances:
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on zbmath.org
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Bibliography
2025
RandONets: Shallow networks with random projections for learning linear and nonlinear operators.
J. Comput. Phys., 2025
Integrating supervised and unsupervised learning approaches to unveil critical process inputs.
Comput. Chem. Eng., 2025
2024
Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning.
BMC Bioinform., December, 2024
IEEE Trans. Neural Networks Learn. Syst., May, 2024
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms.
SIAM J. Sci. Comput., 2024
Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets.
SIAM J. Appl. Dyn. Syst., 2024
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era.
J. Comput. Phys., 2024
Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification.
J. Comput. Phys., 2024
Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints.
CoRR, 2024
Conformal Disentanglement: A Neural Framework for Perspective Synthesis and Differentiation.
CoRR, 2024
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems.
CoRR, 2024
On Learning what to Learn: heterogeneous observations of dynamics and establishing (possibly causal) relations among them.
CoRR, 2024
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators.
CoRR, 2024
CoRR, 2024
Comput. Chem. Eng., 2024
2023
Learning Poisson Systems and Trajectories of Autonomous Systems via Poisson Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., November, 2023
Discrete-time nonlinear feedback linearization via physics-informed machine learning.
J. Comput. Phys., November, 2023
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information.
Comput. Chem. Eng., October, 2023
From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics.
Comput. Chem. Eng., October, 2023
Multiscale Model. Simul., September, 2023
Data-driven control of agent-based models: An Equation/Variable-free machine learning approach.
J. Comput. Phys., April, 2023
Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space.
J. Comput. Phys., 2023
AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression.
CoRR, 2023
Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity.
CoRR, 2023
Micro-Macro Consistency in Multiscale Modeling: Score-Based Model Assisted Sampling of Fast/Slow Dynamical Systems.
CoRR, 2023
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling.
CoRR, 2023
Machine Learning for the identification of phase-transitions in interacting agent-based systems.
CoRR, 2023
CoRR, 2023
Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell Bioreactors.
CoRR, 2023
Equation-Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example.
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
Accurate and efficient multiscale simulation of a heterogeneous elastic beam via computation on small sparse patches.
CoRR, 2023
Benchmarking optimality of time series classification methods in distinguishing diffusions.
CoRR, 2023
Physics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data.
CoRR, 2023
Proceedings of the Learning for Dynamics and Control Conference, 2023
2022
Adaptively Detect and Accurately Resolve Macro-scale Shocks in an Efficient Equation-Free Multiscale Simulation.
SIAM J. Sci. Comput., August, 2022
SIAM J. Math. Data Sci., 2022
SIAM J. Sci. Comput., 2022
Numerical Bifurcation Analysis of PDEs From Lattice Boltzmann Model Simulations: a Parsimonious Machine Learning Approach.
J. Sci. Comput., 2022
Two novel families of multiscale staggered patch schemes efficiently simulate large-scale, weakly damped, linear waves.
CoRR, 2022
Unsupervised learning of observation functions in state-space models by nonparametric moment methods.
CoRR, 2022
Black and Gray Box Learning of Amplitude Equations: Application to Phase Field Systems.
CoRR, 2022
Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data.
CoRR, 2022
CoRR, 2022
Staying the course: Locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds.
CoRR, 2022
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach.
CoRR, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
2021
Equation-free patch scheme for efficient computational homogenisation via self-adjoint coupling.
Numerische Mathematik, 2021
CoRR, 2021
Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning.
CoRR, 2021
CoRR, 2021
Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data.
CoRR, 2021
Exploring critical points of energy landscapes: From low-dimensional examples to phase field crystal PDEs.
Commun. Nonlinear Sci. Numer. Simul., 2021
Proceedings of the 2021 American Control Conference, 2021
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
SIAM/ASA J. Uncertain. Quantification, 2020
Transport Map Accelerated Adaptive Importance Sampling, and Application to Inverse Problems Arising from Multiscale Stochastic Reaction Networks.
SIAM/ASA J. Uncertain. Quantification, 2020
Linking Machine Learning with Multiscale Numerics: Data-Driven Discovery of Homogenized Equations.
CoRR, 2020
2019
Designing networks with resiliency to edge failures using two-stage robust optimization.
Eur. J. Oper. Res., 2019
Large-scale simulation of shallow water waves with computation only on small staggered patches.
CoRR, 2019
2018
On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions.
SIAM J. Appl. Dyn. Syst., 2018
J. Nonlinear Sci., 2018
Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion.
CoRR, 2018
An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning.
IEEE Access, 2018
2017
A general CFD framework for fault-resilient simulations based on multi-resolution information fusion.
J. Comput. Phys., 2017
A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion.
J. Comput. Phys., 2017
Good coupling for the multiscale patch scheme on systems with microscale heterogeneity.
J. Comput. Phys., 2017
Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities.
Frontiers Comput. Neurosci., 2017
Entropy, 2017
2016
Accuracy of Patch Dynamics with Mesoscale Temporal Coupling for Efficient Massively Parallel Simulations.
SIAM J. Sci. Comput., 2016
Data-Driven Reduction for a Class of Multiscale Fast-Slow Stochastic Dynamical Systems.
SIAM J. Appl. Dyn. Syst., 2016
SIAM J. Appl. Dyn. Syst., 2016
No equations, no parameters, no variables: data, and the reconstruction of normal forms by learning informed observation geometries.
CoRR, 2016
2015
A Data-Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition.
J. Nonlinear Sci., 2015
2014
A hybrid stochastic-deterministic algorithm for lattice-gas models of catalytic reactions and the computation of TPD spectra.
Comput. Chem. Eng., 2014
2013
SIAM J. Appl. Dyn. Syst., 2013
Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata.
Entropy, 2013
Noisy dynamic simulations in the presence of symmetry: Data alignment and model reduction.
Comput. Math. Appl., 2013
Equation-Free Computations as DDDAS Protocols in the Study of Engineered Granular Crystals.
Proceedings of the International Conference on Computational Science, 2013
2012
Int. J. Geogr. Inf. Sci., 2012
Mathematical modeling and steady-state analysis of a co-ionic-conducting solid oxide fuel cell.
Proceedings of the American Control Conference, 2012
2011
Analysis and Computation of a Discrete KdV-Burgers Type Equation with Fast Dispersion and Slow Diffusion.
SIAM J. Numer. Anal., 2011
Optim. Lett., 2011
A common approach to the computation of coarse-scale steady states and to consistent initialization on a slow manifold.
Comput. Chem. Eng., 2011
2010
Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo.
J. Comput. Phys., 2010
Equation-Free Multiscale Computations in Social Networks: from Agent-Based Modeling to Coarse-Grained Stability and bifurcation Analysis.
Int. J. Bifurc. Chaos, 2010
2009
Analysis of a Stochastic Chemical System Close to a SNIPER Bifurcation of Its Mean-Field Model.
SIAM J. Appl. Math., 2009
An Efficient Newton-Krylov Implementation of the Constrained Runs Scheme for Initializing on a Slow Manifold.
J. Sci. Comput., 2009
2008
Uncertainty Quantification for Atomistic Reaction Models: An Equation-Free Stochastic Simulation Algorithm Example.
Multiscale Model. Simul., 2008
Multiscale Model. Simul., 2008
Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems.
Multiscale Model. Simul., 2008
2007
SIAM J. Sci. Comput., 2007
Deciding the Nature of the Coarse Equation through Microscopic Simulations: The Baby-Bathwater Scheme.
SIAM Rev., 2007
PLoS Comput. Biol., 2007
Variance Reduction for the Equation-Free Simulation of Multiscale Stochastic Systems.
Multiscale Model. Simul., 2007
Template-Based Stabilization of Relative Equilibria in Systems with Continuous Symmetry.
J. Nonlinear Sci., 2007
Projective and coarse projective integration for problems with continuous symmetries.
J. Comput. Phys., 2007
Int. J. Bifurc. Chaos, 2007
2006
SIAM J. Appl. Dyn. Syst., 2006
An equation-Free Approach to Nonlinear Control: Coarse Feedback Linearization with Pole-Placement.
Int. J. Bifurc. Chaos, 2006
An equation-Free Approach to Coupled oscillator Dynamics: the Kuramoto Model Example.
Int. J. Bifurc. Chaos, 2006
A systems-based approach to multiscale computation: Equation-free detection of coarse-grained bifurcations.
Comput. Chem. Eng., 2006
Proceedings of the American Control Conference, 2006
2005
SIAM J. Appl. Dyn. Syst., 2005
Multiscale Model. Simul., 2005
Multiscale Model. Simul., 2005
J. Sci. Comput., 2005
Equation-Free, Effective Computation for Discrete Systems: a Time stepper Based Approach.
Int. J. Bifurc. Chaos, 2005
Comput. Sci. Eng., 2005
Equation-free gaptooth-based controller design for distributed complex/multiscale processes.
Comput. Chem. Eng., 2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the American Control Conference, 2005
Proceedings of the American Control Conference, 2005
2004
Coarse bifurcation Diagrams via Microscopic Simulators: a State-Feedback Control-Based Approach.
Int. J. Bifurc. Chaos, 2004
Bifurcation analysis of nonlinear reaction-diffusion problems using wavelet-based reduction techniques.
Comput. Chem. Eng., 2004
Optimal sensor location and reduced order observer design for distributed process systems.
Comput. Chem. Eng., 2004
The gaptooth scheme, patch dynamics and equation-free controller design for distributed complex/multiscale processes.
Proceedings of the 2004 American Control Conference, 2004
2003
Projective Methods for Stiff Differential Equations: Problems with Gaps in Their Eigenvalue Spectrum.
SIAM J. Sci. Comput., 2003
Comput. Chem. Eng., 2003
Proceedings of the 42nd IEEE Conference on Decision and Control, 2003
Proceedings of the American Control Conference, 2003
Proceedings of the American Control Conference, 2003
Proceedings of the American Control Conference, 2003
2001
The Oseberg Transition: Visualization of Global bifurcations for the Kuramoto-Sivashinsky equation.
Int. J. Bifurc. Chaos, 2001
1997
Unsteady Two-Dimensional Flows in Complex Geometries: Comparative Bifurcation Studies with Global Eigenfunction Expansions.
SIAM J. Sci. Comput., 1997
Two-dimensional invariant manifolds and global bifurcations: some approximation and visualization studies.
Numer. Algorithms, 1997
1993
Identification of Continuous-Time Dynamical Systems: Neural Network Based Algorithms and Parallel Implementation.
Proceedings of the Sixth SIAM Conference on Parallel Processing for Scientific Computing, 1993
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993