Luc Rey-Bellet

SIAM/ASA J. Uncertain. Quantification, 2025

2024

Lipschitz-Regularized Gradient Flows and Generative Particle Algorithms for High-Dimensional Scarce Data.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2024

Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows.

[BibT_eX]

[DOI]

Hyemin Gu

Benjamin J. Zhang

CoRR, 2024

Nonlinear denoising score matching for enhanced learning of structured distributions.

[BibT_eX]

[DOI]

Benjamin J. Zhang

CoRR, 2024

Learning heavy-tailed distributions with Wasserstein-proximal-regularized α-divergences.

[BibT_eX]

[DOI]

Ziyu Chen

Hyemin Gu

CoRR, 2024

2023

Sample Complexity of Probability Divergences under Group Symmetry.

[BibT_eX]

[DOI]

Ziyu Chen

Proceedings of the International Conference on Machine Learning, 2023

Function-space regularized Rényi divergences.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Model Uncertainty and Correctability for Directed Graphical Models.

[BibT_eX]

[DOI]

Panagiota Birmpa

Jinchao Feng

SIAM/ASA J. Uncertain. Quantification, 2022

(f, Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.

[BibT_eX]

[DOI]

Yannis Pantazis

J. Mach. Learn. Res., 2022

Lipschitz regularized gradient flows and latent generative particles.

[BibT_eX]

[DOI]

CoRR, 2022

Structure-preserving GANs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Variational Representations and Neural Network Estimation of Rényi Divergences.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2021

Positive feedback in coordination games: Stochastic evolutionary dynamics and the logit choice rule.

[BibT_eX]

[DOI]

Games Econ. Behav., 2021

2020

How Biased Is Your Model? Concentration Inequalities, Information and Model Bias.

[BibT_eX]

[DOI]

Konstantinos Gourgoulias

IEEE Trans. Inf. Theory, 2020

Uncertainty Quantification for Markov Processes via Variational Principles and Functional Inequalities.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, 2020

Strategic decompositions of normal form games: Zero-sum games and potential games.

[BibT_eX]

[DOI]

Games Econ. Behav., 2020

(f, Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.

[BibT_eX]

[DOI]

Yannis Pantazis

CoRR, 2020

A Variational Formula for Rényi Divergences.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Robustness of Dynamical Quantities of Interest via Goal-Oriented Information Theory.

[BibT_eX]

[DOI]

CoRR, 2019

2017

Scalable information inequalities for uncertainty quantification.

[BibT_eX]

[DOI]

J. Comput. Phys., 2017

Information criteria for quantifying loss of reversibility in parallelized KMC.

[BibT_eX]

[DOI]

Konstantinos Gourgoulias

J. Comput. Phys., 2017

2016

Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo.

[BibT_eX]

[DOI]

Konstantinos Gourgoulias

SIAM J. Sci. Comput., 2016

Simple Characterizations of Potential Games and Zero-sum Games.

[BibT_eX]

[DOI]

CoRR, 2016

2014

Coarse-graining schemes for stochastic lattice systems with short and long-range interactions.

[BibT_eX]

[DOI]

Petr Plechác

Dimitrios K. Tsagkarogiannis

Math. Comput., 2014

2011

Decompositions of two player games: potential, zero-sum, and stable games

[BibT_eX]

[DOI]

CoRR, 2011

2008

Multibody Interactions in Coarse-Graining Schemes for Extended Systems.

[BibT_eX]

[DOI]

Sasanka Are

Petr Plechác

SIAM J. Sci. Comput., 2008

Numerical and Statistical Methods for the Coarse-Graining of Many-Particle Stochastic Systems.

[BibT_eX]

[DOI]

Petr Plechác