323 citations · 324 across the 3 of their papers we have counts for
7 papers · 1 filter
Accuracy controlled data assimilation for parabolic problems
Wolfgang Dahmen, Rob Stevenson, Jan Westerdiep
This paper is concerned with the recovery of (approximate) solutions to parabolic problems from incomplete and possibly inconsistent observational data, given on a time-space cylin…
Nonlinear reduced models for state and parameter estimation
Albert Cohen, Wolfgang Dahmen, Olga Mula +1
State estimation aims at approximately reconstructing the solution to a parametrized partial differential equation from linear measurements, when the parameter vector i…
State Estimation -- The Role of Reduced Models
Albert Cohen, Wolfgang Dahmen, Ron DeVore
The exploration of complex physical or technological processes usually requires exploiting available information from different sources: (i) physical laws often represented as a fa…
Adaptive Low-Rank Approximations for Operator Equations: Accuracy Control and Computational Complexity
Markus Bachmayr, Wolfgang Dahmen
The challenge of mastering computational tasks of enormous size tends to frequently override questioning the quality of the numerical outcome in terms of accuracy. By this we do no…
Optimal reduced model algorithms for data-based state estimation
Albert Cohen, Wolfgang Dahmen, Ron DeVore +3
Reduced model spaces, such as reduced basis and polynomial chaos, are linear spaces of finite dimension which are designed for the efficient approximation of families par…
Reduced Basis Greedy Selection Using Random Training Sets
Albert Cohen, Wolfgang Dahmen, Ronald DeVore
Reduced bases have been introduced for the approximation of parametrized PDEs in applications where many online queries are required. Their numerical efficiency for such problems h…