Numerical and Statistical Methods for the Coarse-Graining of Many-Particle Stochastic Systems. - Markos A. Katsoulakis; Petr Plechác; Luc Rey-Bellet (J. Sci. Comput., 2008)

Multibody Interactions in Coarse-Graining Schemes for Extended Systems. - Sasanka Are; Markos A. Katsoulakis; Petr Plechác; Luc Rey-Bellet (SIAM J. Sci. Comput., 2008)

Decompositions of two player games: potential, zero-sum, and stable games - Sung-Ha Hwang; Luc Rey-Bellet (CoRR, 2011)

Coarse-graining schemes for stochastic lattice systems with short and long-range interactions. - Markos A. Katsoulakis; Petr Plechác; Luc Rey-Bellet; Dimitrios K. Tsagkarogiannis (Math. Comput., 2014)

Simple Characterizations of Potential Games and Zero-sum Games. - Sung-Ha Hwang; Luc Rey-Bellet (CoRR, 2016)

Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet (SIAM J. Sci. Comput., 2016)

Information criteria for quantifying loss of reversibility in parallelized KMC. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet (J. Comput. Phys., 2017)

Scalable information inequalities for uncertainty quantification. - Markos A. Katsoulakis; Luc Rey-Bellet; Jie Wang 030 (J. Comput. Phys., 2017)

Robustness of Dynamical Quantities of Interest via Goal-Oriented Information Theory. - Jeremiah Birrell; Markos A. Katsoulakis; Luc Rey-Bellet (CoRR, 2019)

A Variational Formula for Rényi Divergences. - Jeremiah Birrell; Paul Dupuis; Markos A. Katsoulakis; Luc Rey-Bellet; Jie Wang 030 (CoRR, 2020)

(f, Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics. - Jeremiah Birrell; Paul Dupuis; Markos A. Katsoulakis; Yannis Pantazis; Luc Rey-Bellet (CoRR, 2020)

Strategic decompositions of normal form games: Zero-sum games and potential games. - Sung-Ha Hwang; Luc Rey-Bellet (Games Econ. Behav., 2020)

Uncertainty Quantification for Markov Processes via Variational Principles and Functional Inequalities. - Jeremiah Birrell; Luc Rey-Bellet (SIAM/ASA J. Uncertain. Quantification, 2020)

How Biased Is Your Model? Concentration Inequalities, Information and Model Bias. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet; Jie Wang 030 (IEEE Trans. Inf. Theory, 2020)

Positive feedback in coordination games: Stochastic evolutionary dynamics and the logit choice rule. - Sung-Ha Hwang; Luc Rey-Bellet (Games Econ. Behav., 2021)

Variational Representations and Neural Network Estimation of Rényi Divergences. - Jeremiah Birrell; Paul Dupuis; Markos A. Katsoulakis; Luc Rey-Bellet; Jie Wang 030 (SIAM J. Math. Data Sci., 2021)

Structure-preserving GANs. - Jeremiah Birrell; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (ICML, 2022)

Lipschitz regularized gradient flows and latent generative particles. - Hyemin Gu; Panagiota Birmpa; Yannis Pantazis; Luc Rey-Bellet; Markos A. Katsoulakis (CoRR, 2022)

(f, Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics. - Jeremiah Birrell; Paul Dupuis; Markos A. Katsoulakis; Yannis Pantazis; Luc Rey-Bellet (J. Mach. Learn. Res., 2022)

Model Uncertainty and Correctability for Directed Graphical Models. - Panagiota Birmpa; Jinchao Feng; Markos A. Katsoulakis; Luc Rey-Bellet (SIAM/ASA J. Uncertain. Quantification, 2022)

Function-space regularized Rényi divergences. - Jeremiah Birrell; Yannis Pantazis; Paul Dupuis; Luc Rey-Bellet; Markos A. Katsoulakis (ICLR, 2023)

Sample Complexity of Probability Divergences under Group Symmetry. - Ziyu Chen; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (ICML, 2023)

Learning heavy-tailed distributions with Wasserstein-proximal-regularized α-divergences. - Ziyu Chen; Hyemin Gu; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (CoRR, 2024)

Nonlinear denoising score matching for enhanced learning of structured distributions. - Jeremiah Birrell; Markos A. Katsoulakis; Luc Rey-Bellet; Benjamin J. Zhang; Wei Zhu 007 (CoRR, 2024)

Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows. - Hyemin Gu; Markos A. Katsoulakis; Luc Rey-Bellet; Benjamin J. Zhang (CoRR, 2024)

Lipschitz-Regularized Gradient Flows and Generative Particle Algorithms for High-Dimensional Scarce Data. - Hyemin Gu; Panagiota Birmpa; Yannis Pantazis; Luc Rey-Bellet; Markos A. Katsoulakis (SIAM J. Math. Data Sci., 2024)

Statistical Guarantees of Group-Invariant GANs. - Ziyu Chen; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (SIAM/ASA J. Uncertain. Quantification, 2025)