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\u53c2\u8003\u8d44\u6599<\/span><\/strong>\uff1a<\/span><\/h3>\n

[1] Erik Hoel, Larissa Albantakis, and Giulio Tononi. 2013. \u201cQuantifying Causal Emergence Shows That Macro Can Beat Micro.\u201d Proceedings of the National Academy of Sciences of the United States of America 110 (49): 19790\u201395.<\/span><\/p>\n

[2] Brennan Klein and Erik Hoel. 2020. \u201cThe Emergence of Informative Higher Scales in Complex Networks.\u201d Complexity 2020 (2020): 1\u201312.<\/span><\/p>\n

[3] Ross Griebenow, Brennan Klein, and Erik Hoel. 2019. \u201cFinding the Right Scale of a Network: Efficient Identification of Causal Emergence through Spectral Clustering.\u201d ArXiv Preprint ArXiv:1908.07565.<\/span><\/p>\n


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[1] Hoel, E. P., Albantakis, L., & Tononi, G. (2013). Quantifying causal emergence shows that macro can beat micro. Proceedings of the National Academy of Sciences of the United States of America, 110(49), 19790\u201319795. https:\/\/doi.org\/10.1073\/pnas.1314922110<\/span><\/p>\n

[2] Marrow, S., Michaud, E. J., & Hoel, E. (2020). Examining the causal structures of deep neural networks using information theory. Entropy, 22(12), 1\u201314. https:\/\/doi.org\/10.3390\/e22121429<\/span><\/p>\n


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[1] Brennan Klein and Erik Hoel. 2020. \u201cThe Emergence of Informative Higher Scales in Complex Networks.\u201d Complexity 2020 (2020): 1\u201312.<\/span><\/p>\n

[2] Wang, Lin-Chuan, Xue-Fei Tang, and Li-Jia Zhang. “Aspect-oriented: a candidate for the biologically-inspired programming paradigm for neural networks and evolvable software.” Huang et al.[581].<\/span><\/p>\n


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