TY  - JOUR
A1  - Reich, Sebastian
T1  - Data assimilation
T2  - Acta numerica
N2  - Data assimilation addresses the general problem of how to combine model-based predictions with partial and noisy observations of the process in an optimal manner. This survey focuses on sequential data assimilation techniques using probabilistic particle-based algorithms. In addition to surveying recent developments for discrete- and continuous-time data assimilation, both in terms of mathematical foundations and algorithmic implementations, we also provide a unifying framework from the perspective of coupling of measures, and Schrödinger’s boundary value problem for stochastic processes in particular.
Y1  - 2019
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/50601
SN  - 0962-4929
SN  - 1474-0508
VL  - 28
SP  - 635
EP  - 711
PB  - Cambridge Univ. Press
CY  - New York
ER  -