14 citations · 30 across the 6 of their papers we have counts for
4 papers · 1 filter
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction
Yingfang Yuan, Wenjun Wang, Wei Pang
Recently, the study of graph neural network (GNN) has attracted much attention and achieved promising performance in molecular property prediction. Most GNNs for molecular property…
A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks
Yingfang Yuan, Wenjun Wang, Wei Pang
In recent years, graph neural networks (GNNs) have gained increasing attention, as they possess the excellent capability of processing graph-related problems. In practice, hyperpar…
A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks
Yingfang Yuan, Wenjun Wang, George M. Coghill +1
Graph representation of structured data can facilitate the extraction of stereoscopic features, and it has demonstrated excellent ability when working with deep learning systems, t…
DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence
Edvinas Byla, Wei Pang
In this paper we propose DeepSwarm, a novel neural architecture search (NAS) method based on Swarm Intelligence principles. At its core DeepSwarm uses Ant Colony Optimization (ACO)…