From Anthropocene to Artificial Intelligence? Challenges of Machine Learning for Science, Life, and Society

[1]  K. Mainzer.  Künstliche Intelligenz – Wann übernehmen die Maschinen? , 2016 .

[2]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[3]  David Easley,et al.  Networks, Crowds, and Markets by David Easley , 2010 .

[4]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[5]  Jure Leskovec,et al.  The dynamics of viral marketing , 2005, EC '06.

[6]  David Easley,et al.  Networks, Crowds, and Markets: Network Dynamics: Structural Models , 2010 .

[7]  K. Mainzer.  Die Berechnung der Welt , 2014 .

[8]  Jared Dean,et al.  Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners , 2014 .

[9]  Klaus Mainzer,et al.  Thinking in complexity - the computational dynamics of matter, mind, and mankind, 5th Edition , 2013, Springer complexity.

[10]  Geoffrey E. Hinton,et al.  Parallel Models of Associative Memory , 1989 .

[11]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[12]  F. Weiling.  Lotka, A. J.: Elements of Mathematical Biology. Dover Publications Inc., New‐York 1956; XXX + 465 S., 72 Abb., 36 Tabellen und 4 Übersichtstabellen im Anhang, Preis $ 2,45 , 1965 .

[13]  P. Mcelroy,et al.  Transmission network analysis to complement routine tuberculosis contact investigations. , 2007, American journal of public health.

[14]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[15]  J. Kleinberg,et al.  Networks, Crowds, and Markets , 2010 .