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Ioannis G. Kevrekidis

  1. Physics-informed machine learning
    2021/05/24 by George Em Karniadakis, Ioannis G. Kevrekidis, Lu Lu +3 · 317 citations
    Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #Gaussian Processes and Bayesian Inference #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks
  2. A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition
    2015/06/04 by Matthew O. Williams, Ioannis G. Kevrekidis, Clarence W. Rowley · 94 citations
    Physics and Astronomy · Computer Science · Materials Science · #Model Reduction and Neural Networks #Neural Networks and Reservoir Computing #Machine Learning in Materials Science
  3. Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
    2017/10/01 by Qianxiao Li, Felix Dietrich, Erik M. Bollt +1 · 30 citations
    Engineering · Physics and Astronomy · #Fluid Dynamics and Vibration Analysis #Model Reduction and Neural Networks #Nuclear Engineering Thermal-Hydraulics
  4. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems
    2005/03/22 by Boaz Nadler, Nadler, Boaz, Stéphane Lafon +5 · 11 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #62h30 #65c40 #Diffusion and Search Dynamics #FOS: Mathematics #Mathematical Dynamics and Fractals #Numerical Analysis (math.NA) #Probability (math.PR) #Topological and Geometric Data Analysis
  5. Reduced models in chemical kinetics via nonlinear data-mining
    2013/07/25 by Eliodoro Chiavazzo, C. W. Gear, Chiavazzo, Eliodoro +7 · 4 citations
    Chemical Engineering · Computer Science · Engineering · #Advanced Combustion Engine Technologies #Combustion and flame dynamics #Dynamical Systems (math.DS) #FOS: Mathematics #Nonlinear Dynamics and Pattern Formation
  6. Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data
    2022/05/26 by Seung‐Joon Lee, Lee, Seungjoon, Yorgos M. Psarellis +5 · 6 citations
    Mathematics · Computer Science · Physics and Astronomy · #Mathematical Biology Tumor Growth #Gaussian Processes and Bayesian Inference #Model Reduction and Neural Networks
  7. Equation-Free Multiscale Computation: enabling microscopic simulators to perform system-level tasks
    2002/09/10 by Ioannis G. Kevrekidis, C. W. Gear, C. William Gear +11 · 6 citations
    Computer Science · Engineering · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks #physics.comp-ph
  8. Learning Parametric Koopman Decompositions for Prediction and Control
    2023/10/02 by Yue Guo, Milan Korda, Guo, Yue +5 · 5 citations
    Physics and Astronomy · #Model Reduction and Neural Networks
  9. Neural Chaos: A Spectral Stochastic Neural Operator
    2025/02/17 by Bahador Bahmani, Bahmani, Bahador, Ioannis G. Kevrekidis +3 · 13 citations
    Computer Science · #Computational Engineering #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Machine Learning (stat.ML) #Neural Networks and Applications #and Science (cs.CE)
  10. On the acceleration of spatially distributed agent-based computations: a patch dynamics scheme
    2014/04/29 by Ping Liu, Giovanni Samaey, Liu, Ping +5 · 2 citations
    Computer Science · Mathematics · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #FOS: Mathematics #Mathematical Biology Tumor Growth #Numerical Analysis (math.NA) #Theoretical and Computational Physics
  11. On the Parameter Combinations That Matter and on Those That do Not
    2021/10/13 by Nikolaos Evangelou, Noah J. Wichrowski, Evangelou, Nikolaos +11 · 3 citations
    Computer Science · Physics and Astronomy · #37E99 (Primary) #68T07 (Secondary) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
  12. A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
    2022/11/22 by Danimir T. Doncevic, Doncevic, Danimir T., Alexander Mitsos +11 · 3 citations
    Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA)
  13. Damping factors for the gap-tooth scheme
    2003/10/02 by Giovanni Samaey, Samaey, Giovanni, Ioannis G. Kevrekidis +3 · 2 citations
    Computer Science · Engineering · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #Advanced Numerical Methods in Computational Mathematics #Composite Material Mechanics #physics.comp-ph
  14. The gap-tooth scheme for homogenization problems
    2003/12/01 by Giovanni Samaey, Samaey, Giovanni, Dirk Roose +3 · 1 citation
    Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #physics.comp-ph
  15. Patch dynamics with buffers for homogenization problems
    2004/12/01 by Giovanni Samaey, Samaey, Giovanni, Ioannis G. Kevrekidis +3 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #Advanced Numerical Methods in Computational Mathematics #Composite Material Mechanics #Computational Physics (physics.comp-ph) #FOS: Physical sciences #physics.comp-ph
  16. An Equation-Free Approach to Nonlinear Control: Coarse Feedback Linearization With Pole-Placement
    2004/12/01 by C. I. Siettos, Constantinos Siettos, I. G. Kevrekidis +6 · 1 citation
    Engineering · Materials Science · Physics and Astronomy · #Block Copolymer Self-Assembly #Cellular Automata and Lattice Gases (nlin.CG) #FOS: Physical sciences #Phase Equilibria and Thermodynamics #Theoretical and Computational Physics #nlin.CG
  17. Analysis of a stochastic chemical system close to a SNIPER bifurcation of its mean-field model
    2008/07/28 by Radek Erban, S. Jonathan Chapman, Erban, Radek +5 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Chemistry · Physics and Astronomy · #Chemical Physics (physics.chem-ph) #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Gene Regulatory Network Analysis #stochastic dynamics and bifurcation #thermodynamics and calorimetric analyses
  18. iMapD: intrinsic Map Dynamics exploration for uncharted effective free energy landscapes
    2016/12/31 by Eliodoro Chiavazzo, Ronald R. Coifman, Chiavazzo, Eliodoro +11 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Materials Science · Physics and Astronomy · #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Protein Structure and Dynamics #Theoretical and Computational Physics
  19. On Matching, and Even Rectifying, Dynamical Systems through Koopman\n Operator Eigenfunctions
    2017/12/19 by Erik M. Bollt, Bollt, Erik M., Qianxiao Li +5 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Computational Physics and Python Applications #Dynamical Systems (math.DS) #FOS: Mathematics #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks
  20. Identifying Equivalent Training Dynamics
    2023/02/17 by William T. Redman, Juan M. Bello-Rivas, Redman, William T. +10 · 1 voice · 1 citation
    Computer Science · Mathematics · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #cs.AI #cs.LG #math.DS
  21. Fast-Slow Neural Networks for Learning Singularly Perturbed Dynamical Systems
    2024/02/24 by Daniel A. Serino, Allen Alvarez Loya, Serino, Daniel A. +7 · 2 citations
    Mathematics · #Computational Physics (physics.comp-ph) #Differential Equations and Numerical Methods #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Mathematical Biology Tumor Growth
  22. Algorithmic (Semi-)Conjugacy via Koopman Operator Theory
    2022/09/14 by William T. Redman, Maria Fonoberova, Redman, William T. +7 · 1 citation
    Computer Science · Physics and Astronomy · #Data Structures and Algorithms (cs.DS) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Image and Signal Denoising Methods #Model Reduction and Neural Networks #Neural Networks and Applications
  23. Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets
    2023/03/31 by Aiqing Zhu, Zhu, Aiqing, Tom Bertalan +7 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Reservoir Engineering and Simulation Methods
  24. Enabling Local Neural Operators to perform Equation-Free System-Level Analysis
    2025/05/05 by Gianluca Fabiani, Fabiani, Gianluca, Hannes Vandecasteele +7 · 5 citations
    Physics and Astronomy · Computer Science · Materials Science · #35B40 #37M20 #37N30 #41A35 #47J25 #62M45 #65F15 #65J15 #65J22 #65P30 #68T05 #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #G.1.10 #G.1.3 #G.1.5 #G.1.8 #G.4 #I.2.6 #I.6.5 #J.2 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
  25. AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression
    2023/12/21 by Mario De Florio, Ioannis G. Kevrekidis, De Florio, Mario +3 · 1 citation
    Computer Science · #34A34 #34A55 #70K55 #Chaotic Dynamics (nlin.CD) #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #G.1.7 #I.2.0 #J.2 #Machine Learning (cs.LG) #Neural Networks and Applications #Statistics and Probability (physics.data-an) #Time Series Analysis and Forecasting
  26. Self-similar blow-up solutions in the generalized Korteweg-de Vries equation: Spectral analysis, normal form and asymptotics
    2023/10/20 by S. Jonathan Chapman, Michail E. Kavousanakis, Chapman, S. Jon +7 · 1 citation
    Mathematics · Physics and Astronomy · #Advanced Mathematical Physics Problems #FOS: Physical sciences #Nonlinear Photonic Systems #Nonlinear Waves and Solitons #Pattern Formation and Solitons (nlin.PS)
  27. On Learning what to Learn: heterogeneous observations of dynamics and establishing (possibly causal) relations among them
    2024/06/10 by David W. Sroczynski, Felix Dietrich, Sroczynski, David W. +11 · 1 citation
    Arts and Humanities · Decision Sciences · #Complex Systems and Decision Making #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Philosophy and History of Science
  28. Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do?
    2025/03/05 by Anastasia Georgiou, Daniel Jungen, Georgiou, Anastasia +11 · 2 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Optimization and Control (math.OC)
  29. A Mechanistic Analysis of Transformers for Dynamical Systems
    2025/12/24 by Gregory Duthé, Nikolaos Evangelou, Duthé, Gregory +7 · 1 citation
    Computer Science · Environmental Science · Physics and Astronomy · #Computational Engineering #Ecosystem dynamics and resilience #FOS: Computer and information sciences #Finance #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Reservoir Computing #and Science (cs.CE)
  30. Active search for Bifurcations
    2024/06/17 by Yorgos M. Psarellis, Psarellis, Yorgos M., Themistoklis P. Sapsis +3 · 1 citation
    Computer Science · #Metaheuristic Optimization Algorithms Research #Artificial Intelligence in Games
  31. Blow-up Parameter Landscapes for Polynomial Dynamical Systems
    2026/07/15 by Emil Graf, Ioannis G. Kevrekidis, Alex Townsend
    #math.DS #math.AG