Markos A. Katsoulakis

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 45

Top Topics

Information Theory

Statistical Estimation

Kullback Leibler

Top Venues

J. Comput. Phys.

SIAM/ASA J. Uncertain. Quantification

IEEE Trans. Inf. Theory

Publications

Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Benjamin J. Zhang, Wei Zhu
Nonlinear denoising score matching for enhanced learning of structured distributions. CoRR (2024)
Benjamin J. Zhang, Siting Liu, Wuchen Li, Markos A. Katsoulakis, Stanley J. Osher
Wasserstein proximal operators describe score-based generative models and resolve memorization. CoRR (2024)
Hyemin Gu, Markos A. Katsoulakis, Luc Rey-Bellet, Benjamin J. Zhang
Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows. CoRR (2024)
Nikiforos Mimikos-Stamatopoulos, Benjamin J. Zhang, Markos A. Katsoulakis
Score-based generative models are provably robust: an uncertainty quantification perspective. CoRR (2024)
Ziyu Chen, Hyemin Gu, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu
Learning heavy-tailed distributions with Wasserstein-proximal-regularized α-divergences. CoRR (2024)
Ziyu Chen, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu
Sample Complexity of Probability Divergences under Group Symmetry. ICML (2023)
Benjamin J. Zhang, Markos A. Katsoulakis
A mean-field games laboratory for generative modeling. CoRR (2023)
Yannis Pantazis, Dipjyoti Paul, Michail Fasoulakis, Yannis Stylianou, Markos A. Katsoulakis
Cumulant GAN. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
Ziyu Chen, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu
Statistical Guarantees of Group-Invariant GANs. CoRR (2023)
Jeremiah Birrell, Yannis Pantazis, Paul Dupuis, Luc Rey-Bellet, Markos A. Katsoulakis
Function-space regularized Rényi divergences. ICLR (2023)
Jeremiah Birrell, Markos A. Katsoulakis, Yannis Pantazis
Optimizing Variational Representations of Divergences and Accelerating Their Statistical Estimation. IEEE Trans. Inf. Theory 68 (7) (2022)
Jeremiah Birrell, Yannis Pantazis, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet
Function-space regularized Rényi divergences. CoRR (2022)
Hyemin Gu, Panagiota Birmpa, Yannis Pantazis, Luc Rey-Bellet, Markos A. Katsoulakis
Lipschitz regularized gradient flows and latent generative particles. CoRR (2022)
Panagiota Birmpa, Jinchao Feng, Markos A. Katsoulakis, Luc Rey-Bellet
Model Uncertainty and Correctability for Directed Graphical Models. SIAM/ASA J. Uncertain. Quantification 10 (4) (2022)
Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet
(f, Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics. J. Mach. Learn. Res. 23 (2022)
Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu
Structure-preserving GANs. ICML (2022)
Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu
Structure-preserving GANs. CoRR (2022)
Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
Graph-Informed Neural Networks. AAAI Spring Symposium: MLPS (2021)
Panagiota Birmpa, Jinchao Feng, Markos A. Katsoulakis, Luc Rey-Bellet
Model Uncertainty and Correctability for Directed Graphical Models. CoRR (2021)
Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky
GINNs: Graph-Informed Neural Networks for multiscale physics. J. Comput. Phys. 433 (2021)
Panagiota Birmpa, Markos A. Katsoulakis
Uncertainty Quantification for Markov Random Fields. SIAM/ASA J. Uncertain. Quantification 9 (4) (2021)
Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
Variational Representations and Neural Network Estimation of Rényi Divergences. SIAM J. Math. Data Sci. 3 (4) (2021)
Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
Mutual information for explainable deep learning of multiscale systems. J. Comput. Phys. 444 (2021)
Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
A Variational Formula for Rényi Divergences. CoRR (2020)
Yannis Pantazis, Dipjyoti Paul, Michail Fasoulakis, Yannis Stylianou, Markos A. Katsoulakis
Cumulant GAN. CoRR (2020)
Panagiota Birmpa, Markos A. Katsoulakis
Uncertainty quantification for Markov Random Fields. CoRR (2020)
Markos A. Katsoulakis, Pedro Vilanova
Data-driven, variational model reduction of high-dimensional reaction networks. J. Comput. Phys. 401 (2020)
Jeremiah Birrell, Markos A. Katsoulakis, Yannis Pantazis
Optimizing variational representations of divergences and accelerating their statistical estimation. CoRR (2020)
Søren Taverniers, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
Mutual Information for Explainable Deep Learning of Multiscale Systems. CoRR (2020)
Eric Joseph Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky
GINNs: Graph-Informed Neural Networks for Multiscale Physics. CoRR (2020)
Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet
(f, Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics. CoRR (2020)
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
How Biased Is Your Model? Concentration Inequalities, Information and Model Bias. IEEE Trans. Inf. Theory 66 (5) (2020)
Kimoon Um, Eric Joseph Hall, Markos A. Katsoulakis, Daniel M. Tartakovsky
Causality and Bayesian Network PDEs for multiscale representations of porous media. J. Comput. Phys. 394 (2019)
Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet
Robustness of Dynamical Quantities of Interest via Goal-Oriented Information Theory. CoRR (2019)
Vagelis Harmandaris, Evangelia Kalligiannaki, Markos A. Katsoulakis
Computational Design of Complex Materials Using Information Theory: From Physics- to Data-driven Multi-scale Molecular Models. ERCIM News 2018 (115) (2018)
Eric Joseph Hall, Markos A. Katsoulakis
Robust Information Divergences for Model-Form Uncertainty Arising from Sparse Data in Random PDE. SIAM/ASA J. Uncertain. Quantification 6 (4) (2018)
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet
Information criteria for quantifying loss of reversibility in parallelized KMC. J. Comput. Phys. 328 (2017)
Markos A. Katsoulakis, Nicholas Zabaras
Special Issue: Predictive multiscale materials modeling. J. Comput. Phys. 338 (2017)
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
How biased is your model? Concentration Inequalities, Information and Model Bias. CoRR (2017)
Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
Scalable information inequalities for uncertainty quantification. J. Comput. Phys. 336 (2017)
Vagelis Harmandaris, Evangelia Kalligiannaki, Markos A. Katsoulakis, Petr Plechác
Path-space variational inference for non-equilibrium coarse-grained systems. J. Comput. Phys. 314 (2016)
Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Petr Plechác
Path-Space Information Bounds for Uncertainty Quantification and Sensitivity Analysis of Stochastic Dynamics. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang
Scalable Information Inequalities for Uncertainty Quantification. CoRR (2016)
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet
Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo. SIAM J. Sci. Comput. 38 (6) (2016)
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet
Information Criteria for quantifying loss of reversibility in parallelized KMC. CoRR (2016)
Anastasios Tsourtis, Yannis Pantazis, Markos A. Katsoulakis, Vagelis Harmandaris
Parametric Sensitivity Analysis for Stochastic Molecular Systems using Information Theoretic Metrics. CoRR (2014)
Giorgos Arampatzis, Markos A. Katsoulakis, Petr Plechác
Parallelization, Processor Communication and Error Analysis in Lattice Kinetic Monte Carlo. SIAM J. Numer. Anal. 52 (3) (2014)
Evangelia Kalligiannaki, Markos A. Katsoulakis, Petr Plechác
Spatial Two-Level Interacting Particle Simulations and Information Theory-Based Error Quantification. SIAM J. Sci. Comput. 36 (2) (2014)
Markos A. Katsoulakis, Petr Plechác, Luc Rey-Bellet, Dimitrios K. Tsagkarogiannis
Coarse-graining schemes for stochastic lattice systems with short and long-range interactions. Math. Comput. 83 (288) (2014)
Yannis Pantazis, Markos A. Katsoulakis, Dionisios G. Vlachos
Parametric Sensitivity Analysis for Biochemical Reaction Networks based on Pathwise Information Theory CoRR (2013)
Yannis Pantazis, Markos A. Katsoulakis, Dionisios G. Vlachos
Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory. BMC Bioinform. 14 (2013)
Markos A. Katsoulakis, Petr Plechác
Information-theoretic tools for parametrized coarse-graining of non-equilibrium extended systems CoRR (2013)
Evangelia Kalligiannaki, Markos A. Katsoulakis, Petr Plechác, Dionisios G. Vlachos
Multilevel coarse graining and nano-pattern discovery in many particle stochastic systems. J. Comput. Phys. 231 (6) (2012)
Giorgos Arampatzis, Markos A. Katsoulakis, Petr Plechác, Michela Taufer, Lifan Xu
Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms. J. Comput. Phys. 231 (23) (2012)
Nasser Mohieddin Abukhdeir, Dionisios G. Vlachos, Markos A. Katsoulakis, Michael Plexousakis
Long-time integration methods for mesoscopic models of pattern-forming systems. J. Comput. Phys. 230 (14) (2011)
Sasanka Are, Markos A. Katsoulakis, Petr Plechác, Luc Rey-Bellet
Multibody Interactions in Coarse-Graining Schemes for Extended Systems. SIAM J. Sci. Comput. 31 (2) (2008)
Markos A. Katsoulakis, Petr Plechác, Luc Rey-Bellet
Numerical and Statistical Methods for the Coarse-Graining of Many-Particle Stochastic Systems. J. Sci. Comput. 37 (1) (2008)
Alexandros Sopasakis, Markos A. Katsoulakis
Stochastic Modeling and Simulation of Traffic Flow: Asymmetric Single Exclusion Process with Arrhenius look-ahead dynamics. SIAM J. Appl. Math. 66 (3) (2006)
Markos A. Katsoulakis, Petr Plechác, Alexandros Sopasakis
Error Analysis of Coarse-Graining for Stochastic Lattice Dynamics. SIAM J. Numer. Anal. 44 (6) (2006)
Markos A. Katsoulakis, Shi Jin
Hyperbolic Systems with Supercharacteristic Relaxations and Roll Waves. SIAM J. Appl. Math. 61 (1) (2000)