Ioannis G. Kevrekidis

ORCID

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 105

Top Venues

CoRR

J. Comput. Phys.

Comput. Chem. Eng.

SIAM J. Appl. Dyn. Syst.

Publications

Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos I. Siettos, Athanasios N. Yannacopoulos
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators. CoRR (2024)
Yorgos M. Psarellis, Themistoklis P. Sapsis, Ioannis G. Kevrekidis
Active search for Bifurcations. CoRR (2024)
David W. Sroczynski, Felix Dietrich, Eleni D. Koronaki, Ronen Talmon, Ronald R. Coifman, Erik M. Bollt, Ioannis G. Kevrekidis
On Learning what to Learn: heterogeneous observations of dynamics and establishing (possibly causal) relations among them. CoRR (2024)
Dimitris G. Giovanis, Dimitrios Loukrezis, Ioannis G. Kevrekidis, Michael D. Shields
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification. CoRR (2024)
Paris Papavasileiou, Dimitrios G. Giovanis, Gabriele Pozzetti, Martin Kathrein, Christoph Czettl, Ioannis G. Kevrekidis, Andreas G. Boudouvis, Stéphane P. A. Bordas, Eleni D. Koronaki
Integrating supervised and unsupervised learning approaches to unveil critical process inputs. CoRR (2024)
Eleni D. Koronaki, Luise F. Kaven, Johannes M. M. Faust, Ioannis G. Kevrekidis, Alexander Mitsos
Nonlinear Manifold Learning Determines Microgel Size from Raman Spectroscopy. CoRR (2024)
Aaron Mahler, Tyrus Berry, Tom Stephens, Harbir Antil, Michael Merritt, Jeanie Schreiber, Ioannis G. Kevrekidis
On-manifold projected gradient descent. Frontiers Comput. Sci. 6 (2024)
Hector Vargas Alvarez, Gianluca Fabiani, Ioannis G. Kevrekidis, Nikolaos Kazantzis, Constantinos I. Siettos
Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks. CoRR (2024)
Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. J. Comput. Phys. 506 (2024)
Antonio Russo, Miguel A. Durán-Olivencia, Ioannis G. Kevrekidis, Serafim Kalliadasis
Machine Learning Memory Kernels as Closure for Non-Markovian Stochastic Processes. IEEE Trans. Neural Networks Learn. Syst. 35 (5) (2024)
Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. SIAM J. Sci. Comput. 46 (2) (2024)
Bahador Bahmani, Somdatta Goswami, Ioannis G. Kevrekidis, Michael D. Shields
A Resolution Independent Neural Operator. CoRR (2024)
Tianqi Cui, Tom Bertalan, Nelson Ndahiro, Pratik Khare, Michael Betenbaugh, Costas Maranas, Ioannis G. Kevrekidis
Data-driven and physics informed modeling of Chinese Hamster Ovary cell bioreactors. Comput. Chem. Eng. 183 (2024)
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos I. Siettos, Ioannis G. Kevrekidis
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning. CoRR (2023)
Aiqing Zhu, Tom Bertalan, Beibei Zhu, Yifa Tang, Ioannis G. Kevrekidis
Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets. CoRR (2023)
Ellis R. Crabtree, Juan M. Bello-Rivas, Ioannis G. Kevrekidis
Micro-Macro Consistency in Multiscale Modeling: Score-Based Model Assisted Sampling of Fast/Slow Dynamical Systems. CoRR (2023)
Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Cristina P. Martin-Linares, Constantinos I. Siettos, Ioannis G. Kevrekidis
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points. CoRR (2023)
Juan M. Bello-Rivas, Anastasia S. Georgiou, Hannes Vandecasteele, Ioannis G. Kevrekidis
Gentlest ascent dynamics on manifolds defined by adaptively sampled point-clouds. CoRR (2023)
Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis
From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics. CoRR (2023)
Saurabh Malani, Tom S. Bertalan, Tianqi Cui, Jose L. Avalos, Michael Betenbaugh, Ioannis G. Kevrekidis
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information. Comput. Chem. Eng. 178 (2023)
Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis, Andreas G. Boudouvis, Ioannis G. Kevrekidis
From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics. Comput. Chem. Eng. 178 (2023)
Tianqi Cui, Tom S. Bertalan, Nelson Ndahiro, Pratik Khare, Michael Betenbaugh, Costas Maranas, Ioannis G. Kevrekidis
Data-driven and Physics Informed Modelling of Chinese Hamster Ovary Cell Bioreactors. CoRR (2023)
Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Ioannis G. Kevrekidis, Mahyar Fazlyab
Certified Invertibility in Neural Networks via Mixed-Integer Programming. CoRR (2023)
Saurabh Malani, Tom S. Bertalan, Tianqi Cui, Jose L. Avalos, Michael Betenbaugh, Ioannis G. Kevrekidis
Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information. CoRR (2023)
Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares, Edriss S. Titi, Ioannis G. Kevrekidis
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era. CoRR (2023)
Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Alexei Makeev, Ioannis G. Kevrekidis
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling. CoRR (2023)
Mario De Florio, Ioannis G. Kevrekidis, George Em Karniadakis
AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression. CoRR (2023)
Nikolaos Evangelou, Dimitrios G. Giovanis, George A. Kevrekidis, Grigorios A. Pavliotis, Ioannis G. Kevrekidis
Machine Learning for the identification of phase-transitions in interacting agent-based systems. CoRR (2023)
Dimitrios G. Patsatzis, Lucia Russo, Ioannis G. Kevrekidis, Constantinos I. Siettos
Data-driven control of agent-based models: An Equation/Variable-free machine learning approach. J. Comput. Phys. 478 (2023)
Erez Peterfreund, Iryna Burak, Ofir Lindenbaum, Jim Gimlett, Felix Dietrich, Ronald R. Coifman, Ioannis G. Kevrekidis
Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity. CoRR (2023)
Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis
Learning Poisson Systems and Trajectories of Autonomous Systems via Poisson Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
Ellis R. Crabtree, Juan M. Bello-Rivas, Andrew L. Ferguson, Ioannis G. Kevrekidis
GANs and Closures: Micro-Macro Consistency in Multiscale Modeling. Multiscale Model. Simul. 21 (3) (2023)
Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space. J. Comput. Phys. 485 (2023)
Cristina P. Martin-Linares, Yorgos M. Psarellis, Georgios Karapetsas, Eleni D. Koronaki, Ioannis G. Kevrekidis
Physics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data. CoRR (2023)
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos I. Siettos, Ioannis G. Kevrekidis
Discrete-time nonlinear feedback linearization via physics-informed machine learning. J. Comput. Phys. 492 (2023)
Aaron Mahler, Tyrus Berry, Tom Stephens, Harbir Antil, Michael Merritt, Jeanie Schreiber, Ioannis G. Kevrekidis
On-Manifold Projected Gradient Descent. CoRR (2023)
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
On Equivalent Optimization of Machine Learning Methods. CoRR (2023)
Matthew O. Williams, Yorgos M. Psarellis, D. Pozharskiy, C. Chong, F. Li, J. Yang, Panayotis G. Kevrekidis, Ioannis G. Kevrekidis
Equation-Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example. CoRR (2023)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC (2022)
Seungjoon Lee, Yorgos M. Psarellis, Constantinos I. Siettos, Ioannis G. Kevrekidis
Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data. CoRR (2022)
Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos, Ioannis G. Kevrekidis, Constantinos I. Siettos
Numerical Bifurcation Analysis of PDEs From Lattice Boltzmann Model Simulations: a Parsimonious Machine Learning Approach. J. Sci. Comput. 92 (2) (2022)
J. Divahar, Anthony J. Roberts, Trent W. Mattner, Judith E. Bunder, Ioannis G. Kevrekidis
Two novel families of multiscale staggered patch schemes efficiently simulate large-scale, weakly damped, linear waves. CoRR (2022)
Felix Dietrich, Or Yair, Rotem Mulayoff, Ronen Talmon, Ioannis G. Kevrekidis
Spectral Discovery of Jointly Smooth Features for Multimodal Data. SIAM J. Math. Data Sci. 4 (1) (2022)
Dimitrios G. Patsatzis, Lucia Russo, Ioannis G. Kevrekidis, Constantinos I. Siettos
Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach. CoRR (2022)
John Maclean, J. E. Bunder, Ioannis G. Kevrekidis, Anthony J. Roberts
Adaptively Detect and Accurately Resolve Macro-scale Shocks in an Efficient Equation-Free Multiscale Simulation. SIAM J. Sci. Comput. 44 (4) (2022)
Yorgos M. Psarellis, Michail E. Kavousanakis, Michael A. Henson, Ioannis G. Kevrekidis
Limits of Entrainment of Circadian Neuronal Networks. CoRR (2022)
Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space. CoRR (2022)
Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. CoRR (2022)
Nikolaos Evangelou, Felix Dietrich, Juan M. Bello-Rivas, Alex Yeh, Rachel Stein, Michael A. Bevan, Ioannis G. Kevrekidis
Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles. CoRR (2022)
J. Divahar, Anthony J. Roberts, Trent W. Mattner, Judith E. Bunder, Ioannis G. Kevrekidis
Staggered grids for multidimensional multiscale modelling. CoRR (2022)
Ellis R. Crabtree, Juan M. Bello-Rivas, Andrew L. Ferguson, Ioannis G. Kevrekidis
GANs and Closures: Micro-Macro Consistency in Multiscale Modeling. CoRR (2022)
Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li
Personalized Algorithm Generation: A Case Study in Learning ODE Integrators. SIAM J. Sci. Comput. 44 (4) (2022)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CoRR (2022)
Felix P. Kemeth, Sergio Alonso, Blas Echebarria, Ted Moldenhawer, Carsten Beta, Ioannis G. Kevrekidis
Black and Gray Box Learning of Amplitude Equations: Application to Phase Field Systems. CoRR (2022)
Juan M. Bello-Rivas, Anastasia S. Georgiou, John Guckenheimer, Ioannis G. Kevrekidis
Staying the course: Locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds. CoRR (2022)
Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos, Ioannis G. Kevrekidis, Constantinos I. Siettos
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach. CoRR (2022)
Yu-Chia Chen, Marina Meila, Ioannis G. Kevrekidis
Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data. CoRR (2021)
J. E. Bunder, Ioannis G. Kevrekidis, Anthony J. Roberts
Equation-free patch scheme for efficient computational homogenisation via self-adjoint coupling. Numerische Mathematik 149 (2) (2021)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR (2021)
Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis
Initializing LSTM internal states via manifold learning. CoRR (2021)
P. Subramanian, Ioannis G. Kevrekidis, P. G. Kevrekidis
Exploring critical points of energy landscapes: From low-dimensional examples to phase field crystal PDEs. Commun. Nonlinear Sci. Numer. Simul. 96 (2021)
Felix Dietrich, Juan M. Bello-Rivas, Ioannis G. Kevrekidis
On the Correspondence between Gaussian Processes and Geometric Harmonics. CoRR (2021)
John Maclean, J. E. Bunder, Ioannis G. Kevrekidis, Anthony J. Roberts
Adaptively detect and accurately resolve macro-scale shocks in an efficient Equation-Free multiscale simulation. CoRR (2021)
Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, Ioannis G. Kevrekidis
Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning. CoRR (2021)
Hassan Arbabi, Felix P. Kemeth, Tom Bertalan, Ioannis G. Kevrekidis
Coarse-grained and Emergent Distributed Parameter Systems from Data. ACC (2021)
Yubin Lu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, Jinqiao Duan
Learning the temporal evolution of multivariate densities via normalizing flows. CoRR (2021)
Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li
Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators. CoRR (2021)
Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis
On the Parameter Combinations That Matter and on Those That do Not. CoRR (2021)
Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, Tom Bertalan, Matan Gavish, Ioannis G. Kevrekidis, Ronald R. Coifman
LOCA: LOcal Conformal Autoencoder for standardized data coordinates. CoRR (2020)
Caroline Moosmüller, Felix Dietrich, Ioannis G. Kevrekidis
A Geometric Approach to the Transport of Discontinuous Densities. SIAM/ASA J. Uncertain. Quantification 8 (3) (2020)
Tom Bertalan, Felix Dietrich, Ioannis G. Kevrekidis
Transformations between deep neural networks. CoRR (2020)
Thomas N. Thiem, Mahdi Kooshkbaghi, Tom Bertalan, Carlo R. Laing, Ioannis G. Kevrekidis
Emergent Spaces for Coupled Oscillators. Frontiers Comput. Neurosci. 14 (2020)
Simon L. Cotter, Ioannis G. Kevrekidis, Paul T. Russell
Transport Map Accelerated Adaptive Importance Sampling, and Application to Inverse Problems Arising from Multiscale Stochastic Reaction Networks. SIAM/ASA J. Uncertain. Quantification 8 (4) (2020)
Or Yair, Felix Dietrich, Rotem Mulayoff, Ronen Talmon, Ioannis G. Kevrekidis
Spectral Discovery of Jointly Smooth Features for Multimodal Data. CoRR (2020)
Hassan Arbabi, Felix P. Kemeth, Tom Bertalan, Ioannis G. Kevrekidis
Coarse-grained and emergent distributed parameter systems from data. CoRR (2020)
Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks. CoRR (2020)
Hassan Arbabi, Ioannis G. Kevrekidis
Particles to Partial Differential Equations Parsimoniously. CoRR (2020)
Felix Dietrich, Thomas N. Thiem, Ioannis G. Kevrekidis
On the Koopman Operator of Algorithms. SIAM J. Appl. Dyn. Syst. 19 (2) (2020)
Felix P. Kemeth, Tom Bertalan, Thomas N. Thiem, Felix Dietrich, Sung Joon Moon, Carlo R. Laing, Ioannis G. Kevrekidis
Learning emergent PDEs in a learned emergent space. CoRR (2020)
Hassan Arbabi, Judith E. Bunder, Giovanni Samaey, Anthony J. Roberts, Ioannis G. Kevrekidis
Linking Machine Learning with Multiscale Numerics: Data-Driven Discovery of Homogenized Equations. CoRR (2020)
Thomas N. Thiem, Mahdi Kooshkbaghi, Tom Bertalan, Carlo R. Laing, Ioannis G. Kevrekidis
Emergent spaces for coupled oscillators. CoRR (2020)
Or Yair, Felix Dietrich, Ronen Talmon, Ioannis G. Kevrekidis
Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation. CoRR (2019)
Felix Dietrich, Thomas N. Thiem, Ioannis G. Kevrekidis
On the Koopman operator of algorithms. CoRR (2019)
Logan R. Matthews, Chrysanthos E. Gounaris, Ioannis G. Kevrekidis
Designing networks with resiliency to edge failures using two-stage robust optimization. Eur. J. Oper. Res. 279 (3) (2019)
J. E. Bunder, J. Divahar, Ioannis G. Kevrekidis, Trent W. Mattner, Anthony J. Roberts
Large-scale simulation of shallow water waves with computation only on small staggered patches. CoRR (2019)
Alexander Holiday, Mahdi Kooshkbaghi, Juan M. Bello-Rivas, C. William Gear, Antonios Zagaris, Ioannis G. Kevrekidis
Manifold learning for parameter reduction. J. Comput. Phys. 392 (2019)
Alexander Mitsos, Jaromil Najman, Ioannis G. Kevrekidis
Correction to: Optimal deterministic algorithm generation. J. Glob. Optim. 73 (2) (2019)
Seungjoon Lee, Mahdi Kooshkbaghi, Konstantinos G. Spiliotis, Constantinos I. Siettos, Ioannis G. Kevrekidis
Coarse-scale PDEs from fine-scale observations via machine learning. CoRR (2019)
Alexander Mitsos, Jaromil Najman, Ioannis G. Kevrekidis
Optimal deterministic algorithm generation. J. Glob. Optim. 71 (4) (2018)
Erik M. Bollt, Qianxiao Li, Felix Dietrich, Ioannis G. Kevrekidis
On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions. SIAM J. Appl. Dyn. Syst. 17 (2) (2018)
Seungjoon Lee, Felix Dietrich, George E. Karniadakis, Ioannis G. Kevrekidis
Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion. CoRR (2018)
Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich, Tom Bertalan, Kevin Höhlein, Qianxiao Li, Erik M. Bollt, Ronen Talmon, Katharina Krischer, Ioannis G. Kevrekidis
An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning. IEEE Access 6 (2018)
Stefan Klus, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis G. Kevrekidis, Christof Schütte, Frank Noé
Data-Driven Model Reduction and Transfer Operator Approximation. J. Nonlinear Sci. 28 (3) (2018)
Paul Villoutreix, Joakim Andén, Bomyi Lim, Hang Lu, Ioannis G. Kevrekidis, Amit Singer, Stanislav Y. Shvartsman
Synthesizing developmental trajectories. PLoS Comput. Biol. 13 (9) (2017)
Anastasia S. Georgiou, Juan M. Bello-Rivas, Charles William Gear, Hau-Tieng Wu, Eliodoro Chiavazzo, Ioannis G. Kevrekidis
An Exploration Algorithm for Stochastic Simulators Driven by Energy Gradients. Entropy 19 (7) (2017)
Seungjoon Lee, Ioannis G. Kevrekidis, George E. Karniadakis
A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion. J. Comput. Phys. 344 (2017)
Seungjoon Lee, Ioannis G. Kevrekidis, George E. Karniadakis
A general CFD framework for fault-resilient simulations based on multi-resolution information fusion. J. Comput. Phys. 347 (2017)
J. E. Bunder, Anthony J. Roberts, Ioannis G. Kevrekidis
Good coupling for the multiscale patch scheme on systems with microscale heterogeneity. J. Comput. Phys. 337 (2017)
Tom Bertalan, Yan Wu, Carlo R. Laing, C. William Gear, Ioannis G. Kevrekidis
Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities. Frontiers Comput. Neurosci. 11 (2017)
Chrysanthos E. Gounaris, Karthikeyan Rajendran, Ioannis G. Kevrekidis, Christodoulos A. Floudas
Designing networks: A mixed-integer linear optimization approach. Networks 68 (4) (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ioannis G. Kevrekidis