FTAT is a fully test-time adaptation method for tabular classification that re-weights predictions by an estimated shifted label distribution, trusts locally consistent test points, and ensembles multiple learning-rate copies of the model.
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Fully Test-time Adaptation for Tabular Data
FTAT is a fully test-time adaptation method for tabular classification that re-weights predictions by an estimated shifted label distribution, trusts locally consistent test points, and ensembles multiple learning-rate copies of the model.