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MatrixFormer: A Foundation Model for Matrix Completion

Dwaipayan Saha et al.
arXiv CS · Papers
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neural-networks
Matrix completion underlies problems from tabular imputation to causal inference, yet existing tabular foundation models treat it as entry-by-entry prediction, repeating context for every target and discarding the matrix's two-dimensional structure. We introduce MatrixFormer, a pre-trained matrix-na
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