Structural Compositional Function Networks: Interpretable Functional Compositions for Tabular Discovery | ScienceToStartup | ScienceToStartup

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References (12)

[1]

Compositional Function Networks: A High-Performance Alternative to Deep Neural Networks with Built-in Interpretability

2025Fang Li

[2]

GANDALF: Gated Adaptive Network for Deep Automated Learning of Features

2022Manu Joseph, Harsh Raj

[3]

TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

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"StructuralCFN brings interpretable AI to tabular data with novel architecture enhancing feature relationships and scientific discovery."

Interpretable Models•Score: 5•View PDF ↗

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Structural Compositional Function Networks: Interpretable Functional Compositions for Tabular Discovery

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Structural Compositional Function Networks: Interpretable Functional Compositions for Tabular Discovery

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