5 citations · 7 across the 4 of their papers we have counts for
4 papers
XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks
Trevor Londt, Xiaoying Gao, Peter Andreae +1
Convolutional Neural Networks (CNNs) continue to achieve great success in classification tasks as innovative techniques and complex multi-path architecture topologies are introduce…
Evolving Character-Level DenseNet Architectures using Genetic Programming
Trevor Londt, Xiaoying Gao, Peter Andreae
DenseNet architectures have demonstrated impressive performance in image classification tasks, but limited research has been conducted on using character-level DenseNet (char-Dense…
Evolving Character-level Convolutional Neural Networks for Text Classification
Trevor Londt, Xiaoying Gao, Bing Xue +1
Character-level convolutional neural networks (char-CNN) require no knowledge of the semantic or syntactic structure of the language they classify. This property simplifies its imp…
PFMFind: a system for discovery of peptide homology and function
Aleksandar Stojmirović, Peter Andreae, Mike Boland +2
Protein Fragment Motif Finder (PFMFind) is a system that enables efficient discovery of relationships between short fragments of protein sequences using similarity search. It suppo…