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Modeling growth and dynamics of neural networks via message passing in Erlang: neural models have a natural home in message passing functional programming languages

Published: 23 September 2011 Publication History

Abstract

Erlang is well suited as a platform for modeling neural dynamics and development. We overview similarities between neural architecture and language paradigms in Erlang, specifically functional programming, message passing, distributed computing and concurrency. We present examples of using Erlang to model neural dynamics and development respectively. Finally, we synthesize these two examples into an artificial retina and then we conclude with an overview of ongoing work.

References

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C Koch, Biophysics of Computation: Information Processing in Single Neurons, Oxford U. Press (1999)
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A Ooyen, Modeling Neural Development, MIT Press (2003)
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D Purves et al. Neuroscience, Third Edition, Sinauer Associates (2004)
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B He (ed.), Neural Engineering, Kluwer Academic (2005)
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O Sporns, Networks of the Brain, MIT Press (2011)
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Joe Armstrong, Programming Erlang Software for a Concurrent World, The Pragmatic Bookshelf (2007)
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G Sher, Erlang: The Unintentional Neural Network Programming Language, Erlagn Factory (2011)
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http://www.trapexit.org/Erlang_and_Neural_Networks
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Open Source Computer Vision, http://opencv.willowgarage.com
[10]
Biologically motivated Artificial Neural Environment, http://github.com/bias/bane

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  1. Modeling growth and dynamics of neural networks via message passing in Erlang: neural models have a natural home in message passing functional programming languages

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    cover image ACM Conferences
    Erlang '11: Proceedings of the 10th ACM SIGPLAN workshop on Erlang
    September 2011
    108 pages
    ISBN:9781450308595
    DOI:10.1145/2034654
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 23 September 2011

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    Author Tags

    1. computer vision
    2. message passing
    3. neural modeling
    4. parallelism and concurrency

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    ICFP '11
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    Acceptance Rates

    Erlang '11 Paper Acceptance Rate 10 of 14 submissions, 71%;
    Overall Acceptance Rate 51 of 68 submissions, 75%

    Upcoming Conference

    ICFP '25
    ACM SIGPLAN International Conference on Functional Programming
    October 12 - 18, 2025
    Singapore , Singapore

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