Estelle Massart
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2026
Expressivity of congruence-based architectures for DNNs on positive-definite matrices
The paper analyzes congruence-based neural architectures for classifying positive-definite matrices, demonstrating that common semi-orthogonality constraints severely limit the model's expressivity.
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