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Paper detail

Towards Programming Adaptive Linear Neural Networks Through Chemical Reaction Networks

This paper is concerned with programming adaptive linear neural networks (ALNNs) using chemical reaction networks (CRNs) equipped with mass-action kinetics. Through individually programming the forward propagation and the backpropagation of ALNNs, and also utilizing the permeation walls technique, we construct a powerful CRN possessing the function of ALNNs, especially having the function of automatic computation. We also provide theoretical analysis and a case study to support our construction. The results will have potential implications for the developments of synthetic biology, molecular computer and artificial intelligence.

preprint2022arXivOpen access
Yuzhen FanXiaoyu ZhangChuanhou Gao
math.DS
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Yuzhen FanXiaoyu ZhangChuanhou Gao

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