Markos A. Katsoulakis
Orcid: 0000-0003-4354-1766
According to our database1,
Markos A. Katsoulakis
authored at least 49 papers
between 2000 and 2024.
Collaborative distances:
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Bibliography
2024
Equivariant score-based generative models provably learn distributions with symmetries efficiently.
CoRR, 2024
Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows.
CoRR, 2024
Score-based generative models are provably robust: an uncertainty quantification perspective.
CoRR, 2024
Nonlinear denoising score matching for enhanced learning of structured distributions.
CoRR, 2024
Learning heavy-tailed distributions with Wasserstein-proximal-regularized α-divergences.
CoRR, 2024
Wasserstein proximal operators describe score-based generative models and resolve memorization.
CoRR, 2024
2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Optimizing Variational Representations of Divergences and Accelerating Their Statistical Estimation.
IEEE Trans. Inf. Theory, 2022
SIAM/ASA J. Uncertain. Quantification, 2022
(f, Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.
J. Mach. Learn. Res., 2022
Proceedings of the International Conference on Machine Learning, 2022
2021
SIAM J. Math. Data Sci., 2021
SIAM/ASA J. Uncertain. Quantification, 2021
J. Comput. Phys., 2021
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
IEEE Trans. Inf. Theory, 2020
J. Comput. Phys., 2020
(f, Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics.
CoRR, 2020
2019
J. Comput. Phys., 2019
CoRR, 2019
2018
Robust Information Divergences for Model-Form Uncertainty Arising from Sparse Data in Random PDE.
SIAM/ASA J. Uncertain. Quantification, 2018
Computational Design of Complex Materials Using Information Theory: From Physics- to Data-driven Multi-scale Molecular Models.
ERCIM News, 2018
2017
J. Comput. Phys., 2017
J. Comput. Phys., 2017
2016
Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo.
SIAM J. Sci. Comput., 2016
Path-Space Information Bounds for Uncertainty Quantification and Sensitivity Analysis of Stochastic Dynamics.
SIAM/ASA J. Uncertain. Quantification, 2016
J. Comput. Phys., 2016
2014
Spatial Two-Level Interacting Particle Simulations and Information Theory-Based Error Quantification.
SIAM J. Sci. Comput., 2014
Parallelization, Processor Communication and Error Analysis in Lattice Kinetic Monte Carlo.
SIAM J. Numer. Anal., 2014
Coarse-graining schemes for stochastic lattice systems with short and long-range interactions.
Math. Comput., 2014
Parametric Sensitivity Analysis for Stochastic Molecular Systems using Information Theoretic Metrics.
CoRR, 2014
2013
Information-theoretic tools for parametrized coarse-graining of non-equilibrium extended systems
CoRR, 2013
Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.
BMC Bioinform., 2013
2012
Multilevel coarse graining and nano-pattern discovery in many particle stochastic systems.
J. Comput. Phys., 2012
Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms.
J. Comput. Phys., 2012
2011
J. Comput. Phys., 2011
2008
SIAM J. Sci. Comput., 2008
Numerical and Statistical Methods for the Coarse-Graining of Many-Particle Stochastic Systems.
J. Sci. Comput., 2008
2006
SIAM J. Numer. Anal., 2006
Stochastic Modeling and Simulation of Traffic Flow: Asymmetric Single Exclusion Process with Arrhenius look-ahead dynamics.
SIAM J. Appl. Math., 2006
2000
SIAM J. Appl. Math., 2000