3 papers
cs.LG2026
minAction.net: Energy-First Neural Architecture Design -- From Biological Principles to Systematic Validation
Martin G. Frasch
Modern machine learning optimizes for accuracy without explicit treatment of internal computational cost, even though physical and biological systems operate under intrinsic energy…
cs.LG2026
Minimum-Action Learning: Energy-Constrained Symbolic Model Selection for Physical Law Identification from Noisy Data
Martin G. Frasch
Identifying physical laws from noisy observational data is a central challenge in scientific machine learning. We present Minimum-Action Learning (MAL), a framework that selects sy…
q-bio.NC2023
Brain development dictates energy constraints on neural architecture search: cross-disciplinary insights on optimization strategies
Martin G. Frasch
Present day artificial neural architecture search (NAS) strategies are essentially prediction-error-optimized. That holds true for AI functions in general. From the developmental n…