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Ioannis G. Kevrekidis
Yannis G. Kevrekidis
Person information
- affiliation: Johns Hopkins University, Chemical and Biomolecular Engineering, Baltimore, MD, USA
- affiliation: Princeton University, Department of Chemical Engineering
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2020 – today
- 2025
- [j96]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. Comput. Chem. Eng. 192: 108857 (2025) - [j95]Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos I. Siettos
, Athanasios N. Yannacopoulos:
RandONets: Shallow networks with random projections for learning linear and nonlinear operators. J. Comput. Phys. 520: 113433 (2025) - 2024
- [j94]Yorgos M. Psarellis, Seungjoon Lee, Tapomoy Bhattacharjee, Sujit S. Datta, Juan M. Bello-Rivas, Ioannis G. Kevrekidis:
Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning. BMC Bioinform. 25(1): 337 (2024) - [j93]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: 108594 (2024) - [j92]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) - [j91]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: 112910 (2024) - [j90]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. J. Comput. Phys. 519: 113443 (2024) - [j89]Aiqing Zhu
, Tom Bertalan
, Beibei Zhu, Yifa Tang
, Ioannis G. Kevrekidis:
Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets. SIAM J. Appl. Dyn. Syst. 23(4): 2643-2669 (2024) - [j88]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): 719- (2024) - [j87]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): 6531-6543 (2024) - [c20]William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
Identifying Equivalent Training Dynamics. NeurIPS 2024 - [i77]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 abs/2401.16683 (2024) - [i76]Hector Vargas Alvarez, Gianluca Fabiani, Ioannis G. Kevrekidis, Nikolaos Kazantzis, Constantinos I. Siettos:
Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks. CoRR abs/2402.12360 (2024) - [i75]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 abs/2403.08376 (2024) - [i74]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 abs/2405.07751 (2024) - [i73]Gianluca Fabiani
, Ioannis G. Kevrekidis, Constantinos I. Siettos, Athanasios N. Yannacopoulos:
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators. CoRR abs/2406.05470 (2024) - [i72]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 abs/2406.06812 (2024) - [i71]Yorgos M. Psarellis, Themistoklis P. Sapsis, Ioannis G. Kevrekidis:
Active search for Bifurcations. CoRR abs/2406.11141 (2024) - [i70]Bahador Bahmani, Somdatta Goswami, Ioannis G. Kevrekidis, Michael D. Shields:
A Resolution Independent Neural Operator. CoRR abs/2407.13010 (2024) - [i69]Nicholas Karris, Evangelos A. Nikitopoulos, Ioannis G. Kevrekidis, Seungjoon Lee, Alexander Cloninger:
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems. CoRR abs/2408.01857 (2024) - [i68]George A. Kevrekidis, Eleni D. Koronaki, Yannis G. Kevrekidis:
Conformal Disentanglement: A Neural Framework for Perspective Synthesis and Differentiation. CoRR abs/2408.15344 (2024) - [i67]George A. Kevrekidis, Mauro Maggioni, Soledad Villar, Yannis G. Kevrekidis:
Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints. CoRR abs/2408.16138 (2024) - [i66]Nikolaos Evangelou, Alexander M. Stankovic, Ioannis G. Kevrekidis, Mark K. Transtrum:
Comparing analytic and data-driven approaches to parameter identifiability: A power systems case study. CoRR abs/2412.18663 (2024) - 2023
- [j86]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: 108343 (2023) - [j85]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: 108357 (2023) - [j84]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: 111953 (2023) - [j83]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: 112072 (2023) - [j82]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: 112408 (2023) - [j81]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): 1122-1146 (2023) - [j80]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): 8271-8283 (2023) - [c19]Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Yannis G. Kevrekidis, Mahyar Fazlyab:
Certified Invertibility in Neural Networks via Mixed-Integer Programming. L4DC 2023: 483-496 - [i65]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 abs/2301.11728 (2023) - [i64]Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Ioannis G. Kevrekidis, Mahyar Fazlyab:
Certified Invertibility in Neural Networks via Mixed-Integer Programming. CoRR abs/2301.11783 (2023) - [i63]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 abs/2301.12508 (2023) - [i62]Zehong Zhang, Fei Lu, Esther Xu Fei, Terry Lyons, Yannis G. Kevrekidis, Tom Woolf:
Benchmarking optimality of time series classification methods in distinguishing diffusions. CoRR abs/2301.13112 (2023) - [i61]Anthony J. Roberts, Thien Tran-Duc, Judith E. Bunder, Yannis G. Kevrekidis:
Accurate and efficient multiscale simulation of a heterogeneous elastic beam via computation on small sparse patches. CoRR abs/2301.13145 (2023) - [i60]Juan M. Bello-Rivas, Anastasia S. Georgiou, Hannes Vandecasteele, Ioannis G. Kevrekidis:
Gentlest ascent dynamics on manifolds defined by adaptively sampled point-clouds. CoRR abs/2302.04426 (2023) - [i59]Jennifer Sleeman, David Chung, Chace Ashcraft, Jay Brett, Anand Gnanadesikan, Yannis G. Kevrekidis, Marisa Hughes
, Thomas W. N. Haine, Marie-Aude Pradal, Renske Gelderloos, Caroline Tang, Anshu Saksena, Larry White:
Using Artificial Intelligence to aid Scientific Discovery of Climate Tipping Points. CoRR abs/2302.06852 (2023) - [i58]William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
On Equivalent Optimization of Machine Learning Methods. CoRR abs/2302.09160 (2023) - [i57]Jennifer Sleeman, David Chung, Anand Gnanadesikan, Jay Brett, Yannis G. Kevrekidis, Marisa Hughes
, Thomas W. N. Haine, Marie-Aude Pradal, Renske Gelderloos, Chace Ashcraft, Caroline Tang, Anshu Saksena, Larry White:
A Generative Adversarial Network for Climate Tipping Point Discovery (TIP-GAN). CoRR abs/2302.10274 (2023) - [i56]Hector Vargas Alvarez, Gianluca Fabiani
, Nikolaos Kazantzis, Constantinos I. Siettos, Ioannis G. Kevrekidis:
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning. CoRR abs/2303.08884 (2023) - [i55]Aiqing Zhu, Tom Bertalan, Beibei Zhu, Yifa Tang, Ioannis G. Kevrekidis:
Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets. CoRR abs/2303.17824 (2023) - [i54]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 abs/2304.14214 (2023) - [i53]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 abs/2305.02404 (2023) - [i52]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 abs/2305.03257 (2023) - [i51]Aaron Mahler, Tyrus Berry, Tom Stephens, Harbir Antil, Michael Merritt, Jeanie Schreiber, Ioannis G. Kevrekidis:
On-Manifold Projected Gradient Descent. CoRR abs/2308.12279 (2023) - [i50]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 abs/2309.14334 (2023) - [i49]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 abs/2310.15816 (2023) - [i48]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 abs/2310.19039 (2023) - [i47]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 abs/2311.00797 (2023) - [i46]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 abs/2312.05715 (2023) - [i45]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 abs/2312.13155 (2023) - [i44]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 abs/2312.14237 (2023) - 2022
- [j79]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): 34 (2022) - [j78]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): 1911- (2022) - [j77]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): 2557- (2022) - [j76]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): 410-430 (2022) - [c18]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC 2022: 6006-6011 - [c17]William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
An Operator Theoretic View On Pruning Deep Neural Networks. ICLR 2022 - [i43]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 abs/2201.13323 (2022) - [i42]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 abs/2204.10413 (2022) - [i41]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 abs/2204.12536 (2022) - [i40]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 abs/2205.00286 (2022) - [i39]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 abs/2205.13545 (2022) - [i38]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 abs/2207.03954 (2022) - [i37]Qingci An, Yannis G. Kevrekidis, Fei Lu
, Mauro Maggioni:
Unsupervised learning of observation functions in state-space models by nonparametric moment methods. CoRR abs/2207.05242 (2022) - [i36]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 abs/2207.05779 (2022) - [i35]J. Divahar, Anthony J. Roberts, Trent W. Mattner, Judith E. Bunder, Ioannis G. Kevrekidis:
Staggered grids for multidimensional multiscale modelling. CoRR abs/2207.12623 (2022) - [i34]Ellis R. Crabtree, Juan M. Bello-Rivas, Andrew L. Ferguson, Ioannis G. Kevrekidis:
GANs and Closures: Micro-Macro Consistency in Multiscale Modeling. CoRR abs/2208.10715 (2022) - [i33]Yorgos M. Psarellis, Michail E. Kavousanakis, Michael A. Henson, Ioannis G. Kevrekidis:
Limits of Entrainment of Circadian Neuronal Networks. CoRR abs/2208.11119 (2022) - [i32]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CoRR abs/2209.06374 (2022) - [i31]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 abs/2210.15823 (2022) - [i30]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 abs/2211.12386 (2022) - 2021
- [j75]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: 105679 (2021) - [j74]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): 229-272 (2021) - [c16]Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic:
Applications of Koopman Mode Analysis to Neural Networks. AAAI Spring Symposium: MLPS 2021 - [c15]Hassan Arbabi, Felix P. Kemeth, Tom Bertalan, Ioannis G. Kevrekidis:
Coarse-grained and Emergent Distributed Parameter Systems from Data. ACC 2021: 4063-4068 - [i29]Yu-Chia Chen, Marina Meila, Ioannis G. Kevrekidis:
Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data. CoRR abs/2103.07626 (2021) - [i28]Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis:
Initializing LSTM internal states via manifold learning. CoRR abs/2104.13101 (2021) - [i27]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 abs/2105.01303 (2021) - [i26]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 abs/2106.09004 (2021) - [i25]Yubin Lu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, Jinqiao Duan:
Learning the temporal evolution of multivariate densities via normalizing flows. CoRR abs/2107.13735 (2021) - [i24]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 abs/2108.11568 (2021) - [i23]Felix Dietrich, Juan M. Bello-Rivas, Ioannis G. Kevrekidis:
On the Correspondence between Gaussian Processes and Geometric Harmonics. CoRR abs/2110.02296 (2021) - [i22]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 abs/2110.06717 (2021) - [i21]William T. Redman
, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR abs/2110.14856 (2021) - 2020
- [j73]Thomas N. Thiem
, Mahdi Kooshkbaghi
, Tom Bertalan, Carlo R. Laing, Ioannis G. Kevrekidis:
Emergent Spaces for Coupled Oscillators. Frontiers Comput. Neurosci. 14: 36 (2020) - [j72]Caroline Moosmüller
, Felix Dietrich, Ioannis G. Kevrekidis:
A Geometric Approach to the Transport of Discontinuous Densities. SIAM/ASA J. Uncertain. Quantification 8(3): 1012-1035 (2020) - [j71]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): 1383-1413 (2020) - [j70]Felix Dietrich
, Thomas N. Thiem
, Ioannis G. Kevrekidis:
On the Koopman Operator of Algorithms. SIAM J. Appl. Dyn. Syst. 19(2): 860-885 (2020) - [i20]Or Yair, Felix Dietrich, Rotem Mulayoff, Ronen Talmon, Ioannis G. Kevrekidis:
Spectral Discovery of Jointly Smooth Features for Multimodal Data. CoRR abs/2004.04386 (2020) - [i19]Thomas N. Thiem, Mahdi Kooshkbaghi, Tom Bertalan, Carlo R. Laing, Ioannis G. Kevrekidis:
Emergent spaces for coupled oscillators. CoRR abs/2004.06053 (2020) - [i18]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 abs/2004.07234 (2020) - [i17]Iva Manojlovic, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic:
Applications of Koopman Mode Analysis to Neural Networks. CoRR abs/2006.11765 (2020) - [i16]Tom Bertalan, Felix Dietrich, Ioannis G. Kevrekidis:
Transformations between deep neural networks. CoRR abs/2007.05646 (2020) - [i15]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 abs/2008.11276 (2020) - [i14]Hassan Arbabi, Ioannis G. Kevrekidis:
Particles to Partial Differential Equations Parsimoniously. CoRR abs/2011.04517 (2020) - [i13]Hassan Arbabi, Felix P. Kemeth, Tom Bertalan, Ioannis G. Kevrekidis:
Coarse-grained and emergent distributed parameter systems from data. CoRR abs/2011.08138 (2020) - [i12]Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis:
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks. CoRR abs/2012.03133 (2020) - [i11]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 abs/2012.12738 (2020)
2010 – 2019
- 2019
- [j69]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): 704-720 (2019) - [j68]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: 419-431 (2019) - [j67]Alexander Mitsos
, Jaromil Najman, Ioannis G. Kevrekidis:
Correction to: Optimal deterministic algorithm generation. J. Glob. Optim. 73(2): 465 (2019) - [i10]Or Yair, Felix Dietrich, Ronen Talmon, Ioannis G. Kevrekidis:
Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation. CoRR abs/1906.00616 (2019) - [i9]Felix Dietrich, Thomas N. Thiem, Ioannis G. Kevrekidis:
On the Koopman operator of algorithms. CoRR abs/1907.10807 (2019) - [i8]Seungjoon Lee, Mahdi Kooshkbaghi, Konstantinos G. Spiliotis, Constantinos I. Siettos, Ioannis G. Kevrekidis:
Coarse-scale PDEs from fine-scale observations via machine learning. CoRR abs/1909.05707 (2019) - [i7]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 abs/1912.07815 (2019) - 2018
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An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning. IEEE Access 6: 77402-77413 (2018) - [j65]Alexander Mitsos
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Optimal deterministic algorithm generation. J. Glob. Optim. 71(4): 891-913 (2018) - [j64]Stefan Klus
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Data-Driven Model Reduction and Transfer Operator Approximation. J. Nonlinear Sci. 28(3): 985-1010 (2018) - [j63]