Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Weissmann, Simon"'
Consensus based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivative free sampling method referred to as consensus based sampling (CBS).
Externí odkaz:
http://arxiv.org/abs/2409.03518
Stochastic gradient methods are among the most important algorithms in training machine learning problems. While classical assumptions such as strong convexity allow a simple analysis they are rarely satisfied in applications. In recent years, global
Externí odkaz:
http://arxiv.org/abs/2405.13592
Autor:
Weissmann, Simon, Zech, Jakob
In this paper we propose and analyze a novel multilevel version of Stein variational gradient descent (SVGD). SVGD is a recent particle based variational inference method. For Bayesian inverse problems with computationally expensive likelihood evalua
Externí odkaz:
http://arxiv.org/abs/2402.01320
In inverse problems, the goal is to estimate unknown model parameters from noisy observational data. Traditionally, inverse problems are solved under the assumption of a fixed forward operator describing the observation model. In this article, we con
Externí odkaz:
http://arxiv.org/abs/2401.11948
In recent years, various interacting particle samplers have been developed to sample from complex target distributions, such as those found in Bayesian inverse problems. These samplers are motivated by the mean-field limit perspective and implemented
Externí odkaz:
http://arxiv.org/abs/2312.13889
Autor:
Hanu, Matei, Weissmann, Simon
The ensemble Kalman inversion (EKI), a recently introduced optimisation method for solving inverse problems, is widely employed for the efficient and derivative-free estimation of unknown parameters. Specifically in cases involving ill-posed inverse
Externí odkaz:
http://arxiv.org/abs/2312.13804
Markov Decision Processes (MDPs) are a formal framework for modeling and solving sequential decision-making problems. In finite-time horizons such problems are relevant for instance for optimal stopping or specific supply chain problems, but also in
Externí odkaz:
http://arxiv.org/abs/2310.02671
In this work we propose an adaptive multilevel version of subset simulation to estimate the probability of rare events for complex physical systems. Given a sequence of nested failure domains of increasing size, the rare event probability is expresse
Externí odkaz:
http://arxiv.org/abs/2208.05392
Inverse problems occur in a variety of parameter identification tasks in engineering. Such problems are challenging in practice, as they require repeated evaluation of computationally expensive forward models. We introduce a unifying framework of mul
Externí odkaz:
http://arxiv.org/abs/2204.13732
Autor:
Weissmann, Simon
The ensemble Kalman inversion (EKI) is a particle based method which has been introduced as the application of the ensemble Kalman filter to inverse problems. In practice it has been widely used as derivative-free optimization method in order to esti
Externí odkaz:
http://arxiv.org/abs/2203.17117