all AI news
Causal Falsification of Digital Twins. (arXiv:2301.07210v4 [stat.ME] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Digital twins are virtual systems designed to predict how a real-world
process will evolve in response to interventions. This modelling paradigm holds
substantial promise in many applications, but rigorous procedures for assessing
their accuracy are essential for safety-critical settings. We consider how to
assess the accuracy of a digital twin using real-world data. We formulate this
as causal inference problem, which leads to a precise definition of what it
means for a twin to be "correct" appropriate for many applications. …
accuracy applications arxiv digital digital twin digital twins modelling paradigm process safety safety-critical systems twins virtual world