Explicitly modeling and marginalizing environment variation via generalized random-intercept models produces representations that support robust average prediction across unseen environments and outperform invariant-learning methods in challenging distribution-shift settings.
Mixed-effects modeling with crossed random effects for subjects and items
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Robust Representation Learning through Explicit Environment Modeling
Explicitly modeling and marginalizing environment variation via generalized random-intercept models produces representations that support robust average prediction across unseen environments and outperform invariant-learning methods in challenging distribution-shift settings.