Sebastian Krumscheid
Orcid: 0000-0002-1421-5403
According to our database1,
Sebastian Krumscheid authored at least 26 papers
between 2013 and 2026.
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Bibliography
2026
A Posteriori Error Analysis of Runge-Kutta Discontinuous Galerkin Schemes with SIAC Post-Processing for Nonlinear Convection-Diffusion Systems.
CoRR, April, 2026
PurSAMERE: Reliable Adversarial Purification via Sharpness-Aware Minimization of Expected Reconstruction Error.
CoRR, February, 2026
2025
Nonparametric estimation of homogenized invariant measures from multiscale data via Hermite expansion.
CoRR, October, 2025
An Investigation into the Distribution of Ratios of Particle Solver-based Likelihoods.
CoRR, August, 2025
CoRR, January, 2025
Scalable Method for Bayesian Experimental Design without Integrating over Posterior Distribution.
SIAM/ASA J. Uncertain. Quantification, 2025
The Probability of Tiered Benefit: Partial Identification with Robust and Stable Inference.
Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025
2024
A Fully Parallelized and Budgeted Multilevel Monte Carlo Method and the Application to Acoustic Waves.
SIAM/ASA J. Uncertain. Quantification, 2024
Reliable Uncertainty Quantification for Fiber Orientation in Composite Molding Processes using Multilevel Polynomial Surrogates.
CoRR, 2024
Non-parametric Inference for Diffusion Processes: A Computational Approach via Bayesian Inversion for PDEs.
CoRR, 2024
Multi-objective optimization for multi-agent injection strategies in subsurface CO<sub>2</sub> storage.
CoRR, 2024
Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations.
CoRR, 2024
2023
Copula modeling and uncertainty propagation in field-scale simulation of CO<sub>2</sub> fault leakage.
CoRR, 2023
A Fully Parallelized and Budgeted Multi-Level Monte Carlo Method and the Application to Acoustic Waves.
CoRR, 2023
2022
Statistical Learning of Nonlinear Stochastic Differential Equations from Nonstationary Time Series using Variational Clustering.
Multiscale Model. Simul., December, 2022
Quantifying uncertain system outputs via the multi-level Monte Carlo method - distribution and robustness measures.
CoRR, 2022
2021
On the equivalence of different adaptive batch size selection strategies for stochastic gradient descent methods.
CoRR, 2021
Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation.
CoRR, 2021
2020
Quantifying uncertain system outputs via the multilevel Monte Carlo method - Part I: Central moment estimation.
J. Comput. Phys., 2020
2019
2018
SIAM/ASA J. Uncertain. Quantification, 2018
2015
A new framework for extracting coarse-grained models from time series with multiscale structure.
J. Comput. Phys., 2015
2013
Multiscale Model. Simul., 2013