Author

Pietro Barbiero

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#artificial intelligence Jun 2026

The Standard Interpretable Model: A general theory of interpretable machine learning to deductively design interpretable methods using Lagrangian mechanics

The Standard Interpretable Model is introduced, a general theory grounded in Lagrangian mechanics that enables the deductive design of interpretable methods and offers pedagogical grounding for interpretability curricula and may shift the scientific community's perspective of a discipline that has long been fragmented.

Pietro Barbiero, G. Felice, M. Zarlenga et al. · arXiv.org · 1 citation

#artificial intelligence Preprint Aug 2026

Graphical Design of Interpretable Architectures

A graphical notation for designing interpretable AI architectures, adapted from Penrose tensor notation is introduced, which gives a global view of an architecture and maps one to one onto PyTorch einsum code.

Pietro Barbiero · 0 citations