Prefer a chat interface with context about you and your work?
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation
Out-of-distribution (OOD) generalization is a favorable yet challenging property for deep neural networks. The core challenges lie in the limited availability of source domains that help models learn an invariant representation from the spurious features. Various domain augmentation have been proposed but largely rely on interpolating existing domains and frequently …