Work

Future-Law Shape Beyond Two Moments

Year: 2026

Type: preprint

Abstract: A one-dimensional truth-known discrete kernel compares Gaussian innovations with a moment-matched symmetric Gaussian mixture from one exact start state. Train-only symmetric whitening, hybrid Gaussian-kernel MMD, and directional excess kurtosis are scored on 100 seeds with 512 training and 512 test episodes. At separation 0.88 the null rejected in 6/100 units and the mixture was detected in 98/100. The same target with 256 episodes per pool was detected in 82/120. No entropy, committor, empirical, or biological claim is made.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23864253

Author: Langell, Robin

Language: English

Topic: Neural Networks and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7225121048

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