Neural computing for scientific computing applications-Reference-Cited by-同舟云学术

Neural computing for scientific computing applications

Published:2017-07-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Neuromorphic Computing Symposium
language:
Short-container-title:

Author:

Aimone James B.¹,Parekh Ojas¹,Severa William¹

Affiliation:

1. Sandia National Laboratories

Funder

Sandia National Laboratories

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3183584.3183618

Reference43 articles.

1. James B Aimone. 2017. Exponential scaling of neural algorithms-a future beyond Moore's Law? arXiv preprint arXiv:1705.02042 (2017). James B Aimone. 2017. Exponential scaling of neural algorithms-a future beyond Moore's Law? arXiv preprint arXiv:1705.02042 (2017).

2. The Brain Activity Map Project and the Challenge of Functional Connectomics

3. John R Anderson. 2009. How can the human mind occur in the physical universe? Oxford University Press. John R Anderson. 2009. How can the human mind occur in the physical universe? Oxford University Press.

4. Trevor Bekolay James Bergstra Eric Hunsberger Travis DeWolf Terrence C Stewart Daniel Rasmussen Xuan Choo Aaron Russell Voelker and Chris Eliasmith. 2013. Nengo: a Python tool for building large-scale functional brain models. Frontiers in neuroinformatics 7 (2013). Trevor Bekolay James Bergstra Eric Hunsberger Travis DeWolf Terrence C Stewart Daniel Rasmussen Xuan Choo Aaron Russell Voelker and Chris Eliasmith. 2013. Nengo: a Python tool for building large-scale functional brain models. Frontiers in neuroinformatics 7 (2013).

5. Markus Bläser. 2013. Fast Matrix Multiplication. Number 5 in Graduate Surveys. Theory of Computing Library. http://theoryofcomputing.org/articles/gs005/ Markus Bläser. 2013. Fast Matrix Multiplication. Number 5 in Graduate Surveys. Theory of Computing Library. http://theoryofcomputing.org/articles/gs005/

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