Philipp A. Guth

17 papers Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	On the optimality of dimension truncation error rates for a class of parametric partial differential equations. CoRR Philipp A. Guth, Vesa Kaarnioja
2025	J	`jnl`	Quasi-Monte Carlo Integration for Feedback Control Under Uncertainty. SIAM/ASA J. Uncertain. Quantification Philipp A. Guth, Peter Kritzer, Karl Kunisch
2025	J	`jnl`	Quasi-Monte Carlo for Partial Differential Equations with Generalized Gaussian Input Uncertainty. SIAM J. Numer. Anal. Philipp A. Guth, Vesa Kaarnioja
2024	J	`jnl`	Generalized Dimension Truncation Error Analysis for High-Dimensional Numerical Integration: Lognormal Setting and Beyond. SIAM J. Numer. Anal. Philipp A. Guth, Vesa Kaarnioja
2024	J	`jnl`	One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty. SIAM/ASA J. Uncertain. Quantification Philipp A. Guth, Claudia Schillings, Simon Weissmann
2024	J	`jnl`	Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration. Numerische Mathematik Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan
2024	J	`jnl`	Quasi-Monte Carlo for partial differential equations with generalized Gaussian input uncertainty. CoRR Philipp A. Guth, Vesa Kaarnioja
2024	J	`jnl`	Quasi-Monte Carlo integration for feedback control under uncertainty. CoRR Philipp A. Guth, Peter Kritzer, Karl Kunisch
2023	J	`jnl`	Application of dimension truncation error analysis to high-dimensional function approximation. CoRR Philipp A. Guth, Vesa Kaarnioja
2023	J	`jnl`	Multilevel quasi-Monte Carlo for optimization under uncertainty. Numerische Mathematik Philipp A. Guth, Andreas Van Barel
2022	J	`jnl`	Generalized dimension truncation error analysis for high-dimensional numerical integration: lognormal setting and beyond. CoRR Philipp A. Guth, Vesa Kaarnioja
2022	J	`jnl`	Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration. CoRR Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan
2021	J	`jnl`	A General Framework for Machine Learning based Optimization Under Uncertainty. CoRR Philipp A. Guth, Claudia Schillings, Simon Weissmann
2021	J	`jnl`	A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty. SIAM/ASA J. Uncertain. Quantification Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan
2021	J	`jnl`	Multilevel Quasi-Monte Carlo for Optimization under Uncertainty. CoRR Philipp A. Guth, Andreas Van Barel
2020	J	`jnl`	Ensemble Kalman filter for neural network based one-shot inversion. CoRR Philipp A. Guth, Claudia Schillings, Simon Weissmann
2019	J	`jnl`	A quasi-Monte Carlo Method for an Optimal Control Problem Under Uncertainty. CoRR Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan