On the Incorporation of Box-Constraints for Ensemble Kalman Inversion. - Neil K. Chada; Claudia Schillings; Simon Weissmann (CoRR, 2019)

Ensemble Kalman filter for neural network based one-shot inversion. - Philipp A. Guth; Claudia Schillings; Simon Weissmann (CoRR, 2020)

Consistency analysis of bilevel data-driven learning in inverse problems. - Neil K. Chada; Claudia Schillings; Xin T. Tong; Simon Weissmann (CoRR, 2020)

Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. - Simon Weissmann; Neil K. Chada; Claudia Schillings; Xin T. Tong (CoRR, 2021)

A General Framework for Machine Learning based Optimization Under Uncertainty. - Philipp A. Guth; Claudia Schillings; Simon Weissmann (CoRR, 2021)

Fokker-Planck Particle Systems for Bayesian Inference: Computational Approaches. - Sebastian Reich; Simon Weissmann (SIAM/ASA J. Uncertain. Quantification, 2021)

Multilevel Optimization for Inverse Problems. - Simon Weissmann; Ashia Wilson; Jakob Zech (COLT, 2022)

Gradient flow structure and convergence analysis of the ensemble Kalman inversion for nonlinear forward models. - Simon Weissmann (CoRR, 2022)

Continuous Time Limit of the Stochastic Ensemble Kalman Inversion: Strong Convergence Analysis. - Dirk Blömker; Claudia Schillings; Philipp Wacker; Simon Weissmann (SIAM J. Numer. Anal., 2022)

On the ensemble Kalman inversion under inequality constraints. - Matei Hanu; Simon Weissmann (CoRR, 2023)

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods. - Sara Klein; Simon Weissmann; Leif Döring (ICLR, 2024)

The Ensemble Kalman Filter for Dynamic Inverse Problems. - Simon Weissmann; Neil K. Chada; Xin T. Tong (CoRR, 2024)

On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation. - Simon Weissmann; Jakob Zech (CoRR, 2024)

Almost sure convergence rates of stochastic gradient methods under gradient domination. - Simon Weissmann; Sara Klein; Waïss Azizian; Leif Döring (CoRR, 2024)

Polyak's Heavy Ball Method Achieves Accelerated Local Rate of Convergence under Polyak-Lojasiewicz Inequality. - Sebastian Kassing; Simon Weissmann (CoRR, 2024)

Structure Matters: Dynamic Policy Gradient. - Sara Klein; Xiangyuan Zhang; Tamer Basar; Simon Weissmann; Leif Döring (CoRR, 2024)

Adaptive Multilevel Subset Simulation with Selective Refinement. - Daniel Elfverson; Robert Scheichl; Simon Weissmann; Francisco Alejandro Diaz De la O (SIAM/ASA J. Uncertain. Quantification, 2024)

One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty. - Philipp A. Guth; Claudia Schillings; Simon Weissmann (SIAM/ASA J. Uncertain. Quantification, 2024)

Almost Sure Convergence of Stochastic Gradient Methods under Gradient Domination. - Simon Weissmann; Sara Klein; Waïss Azizian; Leif Döring (Trans. Mach. Learn. Res., 2025)

Clustered KL-barycenter design for policy evaluation. - Simon Weissmann; Till Freihaut; Claire Vernade; Giorgia Ramponi; Leif Döring (CoRR, 2025)

Metropolis-adjusted interacting particle sampling. - Björn Sprungk; Simon Weissmann; Jakob Zech (Stat. Comput., 2025)