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2020 – today
- 2024
[j4]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty. SIAM/ASA J. Uncertain. Quantification 12(2): 614-645 (2024)- [j3]Daniel Elfverson, Robert Scheichl, Simon Weissmann
, Francisco Alejandro Diaz De la O:
Adaptive Multilevel Subset Simulation with Selective Refinement. SIAM/ASA J. Uncertain. Quantification 12(3): 932-963 (2024) - [c2]Sara Klein, Simon Weissmann, Leif Döring:
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods. ICLR 2024 - [i16]Simon Weissmann, Neil K. Chada, Xin T. Tong:
The Ensemble Kalman Filter for Dynamic Inverse Problems. CoRR abs/2401.11948 (2024) - [i15]Simon Weissmann, Jakob Zech:
On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation. CoRR abs/2402.01320 (2024) - [i14]Simon Weissmann, Sara Klein, Waïss Azizian, Leif Döring:
Almost sure convergence rates of stochastic gradient methods under gradient domination. CoRR abs/2405.13592 (2024) - 2023
- [i13]Sara Klein, Simon Weissmann, Leif Döring:
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods. CoRR abs/2310.02671 (2023) - [i12]Matei Hanu, Simon Weissmann:
On the ensemble Kalman inversion under inequality constraints. CoRR abs/2312.13804 (2023) - [i11]Björn Sprungk, Simon Weissmann, Jakob Zech:
Metropolis-adjusted interacting particle sampling. CoRR abs/2312.13889 (2023) - 2022
- [j2]Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann:
Continuous Time Limit of the Stochastic Ensemble Kalman Inversion: Strong Convergence Analysis. SIAM J. Numer. Anal. 60(6): 3181-3215 (2022) - [c1]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. COLT 2022: 5489-5524 - [i10]Simon Weissmann:
Gradient flow structure and convergence analysis of the ensemble Kalman inversion for nonlinear forward models. CoRR abs/2203.17117 (2022) - [i9]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. CoRR abs/2204.13732 (2022) - [i8]Daniel Elfverson, Robert Scheichl, Simon Weissmann, Francisco Alejandro DiazDelaO:
Adaptive multilevel subset simulation with selective refinement. CoRR abs/2208.05392 (2022) - 2021
- [j1]Sebastian Reich, Simon Weissmann:
Fokker-Planck Particle Systems for Bayesian Inference: Computational Approaches. SIAM/ASA J. Uncertain. Quantification 9(2): 446-482 (2021) - [i7]Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann:
Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis. CoRR abs/2107.14508 (2021) - [i6]Simon Weissmann, Neil K. Chada, Claudia Schillings, Xin T. Tong:
Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. CoRR abs/2110.09142 (2021) - [i5]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
A General Framework for Machine Learning based Optimization Under Uncertainty. CoRR abs/2112.11126 (2021) - 2020
- [i4]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
Ensemble Kalman filter for neural network based one-shot inversion. CoRR abs/2005.02039 (2020) - [i3]Neil K. Chada, Claudia Schillings, Xin T. Tong, Simon Weissmann:
Consistency analysis of bilevel data-driven learning in inverse problems. CoRR abs/2007.02677 (2020)
2010 – 2019
- 2019
- [i2]Neil K. Chada, Claudia Schillings, Simon Weissmann:
On the Incorporation of Box-Constraints for Ensemble Kalman Inversion. CoRR abs/1908.00696 (2019) - [i1]Sebastian Reich, Simon Weissmann:
Fokker-Planck particle systems for Bayesian inference: Computational approaches. CoRR abs/1911.10832 (2019)
Coauthor Index
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