On the Effectiveness of Interpretable Feedforward Neural Network-Reference-Cited by-同舟云学术

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On the Effectiveness of Interpretable Feedforward Neural Network

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Li Miles Q.¹,Fung Benjamin C. M.²,Abusitta Adel²

Affiliation:

1. School of Computer Science, McGill University,Montreal,Canada

2. School of Information Studies, McGill University,Montreal,Canada

Funder

NSERC Discovery

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09892343.pdf?arnumber=9892343

Reference32 articles.

1. Adam: A method for stochastic optimization;kingma;ArXiv Preprint,2014

2. Scikit-learn: Machine learning in Python;pedregosa;Journal of Machine Learning Research,2011

3. Automatic differentiation in pytorch;paszke;Neural Information Processing Systems 2017-Autodiff Workshop,0

4. Constructing optimal binary decision trees is np-complete;laurent;Information Processing Letters,1976

5. Axiomatic attribution for deep networks;sundararajan;International Conference on Machine Learning,0

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Bidirectional Feedforward Neural Network Architecture Using the Discretized Neural Memory Ordinary Differential Equation;International Journal of Neural Systems;2024-02-06

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