Topology representing networks
Neural Networks
Self-organizing maps
Data visualisation and manifold mapping using the ViSOM
Neural Networks - New developments in self-organizing maps
A self-organising network that grows when required
Neural Networks - New developments in self-organizing maps
2005 Special Issue: Cross-entropy embedding of high-dimensional data using the neural gas model
Neural Networks - 2005 Special issue: IJCNN 2005
Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets
IEEE Transactions on Neural Networks
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
Interactive visualization and analysis of hierarchical neural projections for data mining
IEEE Transactions on Neural Networks
A new model of self-organizing neural networks and its application in data projection
IEEE Transactions on Neural Networks
ViSOM - a novel method for multivariate data projection and structure visualization
IEEE Transactions on Neural Networks
Nonlinear Principal Manifolds --- Adaptive Hybrid Learning Approaches
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
A robust nonlinear projection method using the neural gas network
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Improved propensity matching for heart failure using neural gas and self-organizing maps
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Visualization of topology representing networks
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Topology representing network map: a new tool for visualization of high-dimensional data
Transactions on computational science I
Multidimensional data visualization applied for user's questionnaire data quality assessment
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Linear projection method based on information theoretic learning
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
Nonlinear projection using geodesic distances and the neural gas network
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
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A high-quality distance preserving output representation is provided to the neural gas (NG) network. The nonlinear mapping is determined concurrently along with the codebook vectors. The adaptation rule for codebook positions in the projection space minimizes a cost function that favors the trustworthy preservation of the local topology. The proposed visualization method, called OVI-NG, is an enhancement over curvilinear component analysis (CCA). The results show that the mapping quality obtained with OVI-NG outperforms the original CCA, in terms of the trustworthiness, continuity, topographic function and topology preservation measures.