Visualisation of tree-structured data through generative probabilistic modelling. - Nikolaos Gianniotis; Peter Tiño (ESANN, 2007)

Metric Properties of Structured Data Visualizations through Generative Probabilistic Modeling. - Peter Tiño; Nikolaos Gianniotis (IJCAI, 2007)

Visualization of Tree-Structured Data Through Generative Topographic Mapping. - Nikolaos Gianniotis; Peter Tiño (IEEE Trans. Neural Networks, 2008)

Visualisation of structured data through generative probabilistic modeling. - Nikolaos Gianniotis (2008)

Visualization of Structured Data via Generative Probabilistic Modeling. - Nikolaos Gianniotis; Peter Tiño (Similarity-Based Clustering, 2009)

Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model. - Nikolaos Gianniotis; Peter Tiño; Steve Spreckley; Somak Raychaudhury (ICANN (1), 2009)

Autoencoding Ground Motion Data for Visualisation. - Nikolaos Gianniotis; Carsten Riggelsen; Nicolas Kühn; Frank Scherbaum (ICANN (2), 2012)

Interpretable magnification factors for topographic maps of high dimensional and structured data. - Nikolaos Gianniotis (CIDM, 2013)

Visualisation of high-dimensional data using an ensemble of neural networks. - Nikolaos Gianniotis; Carsten Riggelsen (CIEL, 2013)

Manifold aligned ground motion prediction equations for regional datasets. - Nikolaos Gianniotis; Nicolas Kuehn; Frank Scherbaum (Comput. Geosci., 2014)

Autoencoding time series for visualisation. - Nikolaos Gianniotis; Sven Dennis Kügler; Peter Tiño; Kai Polsterer; Ranjeev Misra (ESANN, 2015)

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. - Kai Lars Polsterer; Fabian Gieseke; Christian Igel; Bernd Doser; Nikolaos Gianniotis (ESANN, 2016)

A spectral model for multimodal redshift estimation. - Sven Dennis Kügler; Nikolaos Gianniotis; Kai Lars Polsterer (SSCI, 2016)

Model-coupled autoencoder for time series visualisation. - Nikolaos Gianniotis; Sven Dennis Kügler; Peter Tiño; Kai Lars Polsterer (Neurocomputing, 2016)

Approximate variational inference based on a finite sample of Gaussian latent variables. - Nikolaos Gianniotis; Christoph Schnörr; Christian Molkenthin; Sanjay Singh Bora (Pattern Anal. Appl., 2016)

Linear Dimensionality Reduction for Time Series. - Nikolaos Gianniotis (ICONIP (1), 2017)

Efficient Optimization of Echo State Networks for Time Series Datasets. - Jacob Reinier Maat; Nikos Gianniotis; Pavlos Protopapas (IJCNN, 2018)

Mixed Variational Inference. - Nikolaos Gianniotis (IJCNN, 2019)

Positive and Scale Invariant Gaussian Process Latent Variable Model for Astronomical Spectra. - Nikos Gianniotis; Kai L. Polsterer; Iliana Isabel Cortés Pérez (ESANN, 2024)