A new architecture for artificial neural networks called Householder-absolute neural layers, or Han-layers for short, that use Householder reflectors as weight ...
We propose a new architecture for artificial neural networks called Householder-absolute neural layers, or Han-layers for short, that use Householder ...
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Jun 8, 2021 · We propose a neural-layer architecture based on Householder weighting and absolute-value activating, called Householder-absolute neural layer or simply Han- ...
Guided by variability considerations, we propose a new architecture called Householder-absolute neural layers, or Han-layers for short, to build high.
In this paper, we propose a new neural network layer called the Householder Absolute-value Neural layer (or Han-layer), which replaces the dense weight matrix ...
Missing: Trainability. | Show results with:Trainability.
In this paper, we propose a new neighborhood preserving layer which can replace these fully connected layers to improve the network robustness. We demonstrate a ...
This research paper describes a simplistic architecture named as AANN: Absolute Artificial Neural Network, which can be used to create highly interpretable ...
... In this work, we investigate the use of the modulus function, also known as the absolute value function, as an activation function for deep learning models.
Householder-Absolute Neural Layers For High Variability and Deep Trainability. We propose a new architecture for artificial neural networks called Hous... 0 ...
To enhance resource efficiency and model deployability of neural networks, we propose a neural-layer architecture based on Householder weighting and ...