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About this paper
Yurii Parzhyn
The paper proposes an artificial neural network whose units and connections have interdependent internal energy states, allowing learning through reductions of an energy landscape rather than an external optimizer. It defines information as measurable external-energy structure interpreted by the system’s internal-energy model. The framework describes three reductions and an attractor, but reports no implementation or empirical comparison.
Summary by alphaXiv.
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