Simon Weissmann

According to our database, Simon Weissmann authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

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

Structure Matters: Dynamic Policy Gradient.

Sara Klein, Xiangyuan Zhang, Tamer Basar, Simon Weissmann, 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

Almost sure convergence rates of stochastic gradient methods under gradient domination.

Simon Weissmann, Sara Klein, Waïss Azizian, Leif Döring

CoRR, 2024

On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation.

Simon Weissmann, Jakob Zech

CoRR, 2024

The Ensemble Kalman Filter for Dynamic Inverse Problems.

Simon Weissmann, Neil K. Chada, Xin T. Tong

CoRR, 2024

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods.

Sara Klein, Simon Weissmann, Leif Döring

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Metropolis-adjusted interacting particle sampling.

Björn Sprungk, Simon Weissmann, Jakob Zech

CoRR, 2023

On the ensemble Kalman inversion under inequality constraints.

Matei Hanu, Simon Weissmann

CoRR, 2023

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., December, 2022

Gradient flow structure and convergence analysis of the ensemble Kalman inversion for nonlinear forward models.

Simon Weissmann

CoRR, 2022

Multilevel Optimization for Inverse Problems.

Simon Weissmann, Ashia Wilson, Jakob Zech

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Fokker-Planck Particle Systems for Bayesian Inference: Computational Approaches.

Sebastian Reich, Simon Weissmann

SIAM/ASA J. Uncertain. Quantification, 2021

A General Framework for Machine Learning based Optimization Under Uncertainty.

Philipp A. Guth, Claudia Schillings, Simon Weissmann

CoRR, 2021

Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion.

Simon Weissmann, Neil K. Chada, Claudia Schillings, Xin T. Tong

CoRR, 2021

2020

Consistency analysis of bilevel data-driven learning in inverse problems.

Neil K. Chada, Claudia Schillings, Xin T. Tong, Simon Weissmann

CoRR, 2020

Ensemble Kalman filter for neural network based one-shot inversion.

Philipp A. Guth, Claudia Schillings, Simon Weissmann

CoRR, 2020

2019

On the Incorporation of Box-Constraints for Ensemble Kalman Inversion.

Neil K. Chada, Claudia Schillings, Simon Weissmann

CoRR, 2019