Analytically Tractable Inference in Deep Neural Networks

Since its inception, deep learning has been overwhelmingly reliant on backpropagation and gradient-based optimization algorithms in order to learn weight and bias parameter values. Tractable Approximate Gaussian Inference (TAGI) algorithm was shown to be a viable and scalable alternative to backprop...

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Veröffentlicht in:	arXiv.org 2021-03
Hauptverfasser:	Luong-Ha Nguyen, James-A Goulet
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Back propagation Back propagation networks Computer architecture Inference Machine learning Neural networks Optimization
Online-Zugang:	Volltext
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