Claudia Schillings

36 papers Misc 1Journal 35

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Affine Invariant Langevin Dynamics for rare-event sampling. CoRR Deepyaman Chakraborty, Ruben Harris, Rupert Klein, Guillermo Olicón-Méndez, Sebastian Reich, Claudia Schillings
2026	J	`jnl`	An optimal experimental design approach to sensor placement in continuous stochastic filtering. Stat. Comput. Sahani Pathiraja, Claudia Schillings, Philipp Wacker
2026	J	`jnl`	Mixture-Weighted Ensemble Kalman Filter with Quasi-Monte Carlo Transport. CoRR Ilja Klebanov, Claudia Schillings, Dana Wrischnig
2026	J	`jnl`	Reverse Diffusion Sampling with Tensor Train Approximations of Hamilton-Jacobi-Bellman Equations. SIAM J. Sci. Comput. Robert Gruhlke, David Sommer, Max Kirstein, Martin Eigel, Claudia Schillings
2025	J	`jnl`	Accuracy Boost in Ensemble Kalman Inversion via Ensemble Control Strategies. CoRR Ruben Harris, Claudia Schillings
2025	J	`jnl`	Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems. CoRR Robert Gruhlke, Matei Hanu, Claudia Schillings, Philipp Wacker
2025	J	`jnl`	Lattice Rules Meet Kernel Cubature. CoRR Vesa Kaarnioja, Ilja Klebanov, Claudia Schillings, Yuya Suzuki
2025	J	`jnl`	Provable Mixed-Noise Learning with Flow-Matching. CoRR Paul Hagemann, Robert Gruhlke, Bernhard Stankewitz, Claudia Schillings, Gabriele Steidl
2025	J	`jnl`	Quasi-Monte Carlo for Bayesian shape inversion governed by the Poisson problem subject to Gevrey regular domain deformations. CoRR Ana Djurdjevac, Vesa Kaarnioja, Max Orteu, Claudia Schillings
2025	J	`jnl`	Uncertainty quantification for stationary and time-dependent PDEs subject to Gevrey regular random domain deformations. CoRR Ana Djurdjevac, Vesa Kaarnioja, Claudia Schillings, André-Alexander Zepernick
2024	J	`jnl`	Generative Modelling with Tensor Train approximations of Hamilton-Jacobi-Bellman equations. CoRR David Sommer, Robert Gruhlke, Max Kirstein, Martin Eigel, Claudia Schillings
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 Bayesian design of experiment problems governed by parametric PDEs. CoRR Vesa Kaarnioja, Claudia Schillings
2023	J	`jnl`	Ensemble Kalman Inversion for Image Guided Guide Wire Navigation in Vascular Systems. CoRR Matei Hanu, Jürgen Hesser, Guido Kanschat, Javier Moviglia, Claudia Schillings, Jan Stallkamp
2023	J	`jnl`	Ensemble-Based Gradient Inference for Particle Methods in Optimization and Sampling. SIAM/ASA J. Uncertain. Quantification Claudia Schillings, Claudia Totzeck, Philipp Wacker
2023	J	`jnl`	Happy People - Image Synthesis as Black-Box Optimization Problem in the Discrete Latent Space of Deep Generative Models. CoRR Steffen Jung, Jan Christian Schwedhelm, Claudia Schillings, Margret Keuper
2023	J	`jnl`	Subsampling in ensemble Kalman inversion. CoRR Matei Hanu, Jonas Latz, Claudia Schillings
2022	J	`jnl`	Continuous Time Limit of the Stochastic Ensemble Kalman Inversion: Strong Convergence Analysis. SIAM J. Numer. Anal. Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann
2022	J	`jnl`	Ensemble-based gradient inference for particle methods in optimization and sampling. CoRR Claudia Schillings, Claudia Totzeck, Philipp Wacker
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`	Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. CoRR Simon Weissmann, Neil K. Chada, Claudia Schillings, Xin T. Tong
2021	J	`jnl`	Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis. CoRR Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann
2020	J	`jnl`	Consistency analysis of bilevel data-driven learning in inverse problems. CoRR Neil K. Chada, Claudia Schillings, Xin T. Tong, Simon Weissmann
2020	J	`jnl`	Ensemble Kalman filter for neural network based one-shot inversion. CoRR Philipp A. Guth, Claudia Schillings, Simon Weissmann
2020	J	`jnl`	On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems. Numerische Mathematik Claudia Schillings, Björn Sprungk, Philipp Wacker
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
2019	J	`jnl`	On the Incorporation of Box-Constraints for Ensemble Kalman Inversion. CoRR Neil K. Chada, Claudia Schillings, Simon Weissmann
2018	J	`jnl`	A Strongly Convergent Numerical Scheme from Ensemble Kalman Inversion. SIAM J. Numer. Anal. Dirk Blömker, Claudia Schillings, Philipp Wacker
2018	J	`jnl`	Large deformation shape uncertainty quantification in acoustic scattering. Adv. Comput. Math. Ralf Hiptmair, Laura Scarabosio, Claudia Schillings, Christoph Schwab
2017	J	`jnl`	Analysis of the Ensemble Kalman Filter for Inverse Problems. SIAM J. Numer. Anal. Claudia Schillings, Andrew M. Stuart
2017	J	`jnl`	Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties - Comparison of Approaches. SIAM/ASA J. Uncertain. Quantification Dishi Liu, Alexander Litvinenko, Claudia Schillings, Volker Schulz
2015	J	`jnl`	Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks. PLoS Comput. Biol. Claudia Schillings, Mikael Sunnåker, Jörg Stelling, Christoph Schwab
2012	Misc	`conf`	Sparse Approximation Algorithms for High Dimensional Parametric Initial Value Problems. HPSC Markus Hansen, Claudia Schillings, Christoph Schwab