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

Fang Li. Compositional Function Networks: A High-Performance Alternative to Deep Neural Networks with Built-in Interpretability. In Ron P. A. Petrick, Christopher W. Geib, editors, Proceedings of the 2026 AAAI Spring Symposium Series, Burlingame, California, USA, April 7-9, 2026. pages 447-454, AAAI Press, 2026. [doi]

Abstract

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