4 papers · 1 filter
An optimal experimental design approach to sensor placement in continuous stochastic filtering
Sahani Pathiraja, Claudia Schillings, Philipp Wacker
Sequential filtering and spatial inverse problems assimilate data points distributed either temporally (in the case of filtering) or spatially (in the case of spatial inverse probl…
On MAP estimates and source conditions for drift identification in SDEs
Daniel Tenbrinck, Nikolas Uesseler, Philipp Wacker +1
We consider the inverse problem of identifying the drift in an SDE from observations of its solution at distinct time points. We derive a corresponding MAP estimate, we p…
Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies
Tim Roith, Leon Bungert, Philipp Wacker
Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical properties, such as mean-field convergence…
Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems
Robert Gruhlke, Matei Hanu, Claudia Schillings +1
We introduce a gradient-free framework for Bayesian Optimal Experimental Design (BOED) in sequential settings, aimed at complex systems where gradient information is unavailable. O…