16 citations · 28 across the 13 of their papers we have counts for
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cs.NE2019★ 3 cited
DeepLABNet: End-to-end Learning of Deep Radial Basis Networks with Fully Learnable Basis Functions
Andrew Hryniowski, Alexander Wong
From fully connected neural networks to convolutional neural networks, the learned parameters within a neural network have been primarily relegated to the linear parameters (e.g.,…
cs.NE2019★ 1 cited
State of Compact Architecture Search For Deep Neural Networks
Mohammad Javad Shafiee, Andrew Hryniowski, Francis Li +2
The design of compact deep neural networks is a crucial task to enable widespread adoption of deep neural networks in the real-world, particularly for edge and mobile scenarios. Du…
cs.LG2019
Seeing Convolution Through the Eyes of Finite Transformation Semigroup Theory: An Abstract Algebraic Interpretation of Convolutional Neural Networks
Andrew Hryniowski, Alexander Wong
Researchers are actively trying to gain better insights into the representational properties of convolutional neural networks for guiding better network designs and for interpretin…