“…One interpretation of this added noise is that it plays the role of an artificial corruption of
, with unbiased model error
that plays the same role as additional observational noise (Kennedy & O’Hagan,
2001). One can obtain unbiased
by inclusion of models for structural model error within
, for example, learned error models that enforce conservation laws and sparsity (M. E. Levine & Stuart, 2021; Schneider et al.,
2022). The inverse problem can be written as
…”