Out-of-distribution (OOD) generalisation is challenging because it involves
not only learning from empirical data, but also deciding among various notions
of generalisation, e.g., optimising the average-case risk, worst-case risk, or
interpolations thereof. While this choice should in principle be made by the
model operator like medical doctors, this informa