Feb. 7, 2024, 5:43 a.m. | Liangwei Yang Hengrui Zhang Zihe Song Jiawei Zhang Weizhi Zhang Jing Ma Philip S. Yu

cs.LG updates on arXiv.org arxiv.org

This paper answers a fundamental question in artificial neural network (ANN) design: We do not need to build ANNs layer-by-layer sequentially to guarantee the Directed Acyclic Graph (DAG) property. Drawing inspiration from biological intelligence (BI), where neurons form a complex, graph-structured network, we introduce the groundbreaking Cyclic Neural Networks (Cyclic NNs). It emulates the flexible and dynamic graph nature of biological neural systems, allowing neuron connections in any graph-like structure, including cycles. This offers greater adaptability compared to the DAG …

ann anns artificial build cs.lg cs.ne dag design dynamic form graph groundbreaking inspiration intelligence layer network networks neural network neural networks neurons nns paper property question

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