Publication list
Positive and Scale Invariant Gaussian Process Latent Variable Model for Astronomical Spectra
N. Gianniotis, I. Cortés Pérez, K. L. Polsterer
European Symposium on Artificial Neural Networks, 2024 pdf
A Gaussian process cross-correlation approach to time-delay estimation in active galactic nuclei
F. Pozo Nunez, N. Gianniotis, K. L. Polsterer
Astronomy & Astrophysics, 2023 link
Disentangling the optical AGN and host-galaxy luminosity with a probabilistic flux variation gradient
N. Gianniotis, F. Pozo Nunez, K. L. Polsterer
Astronomy & Astrophysics, 2021 pdf
Optical continuum photometric reverberation mapping of the Seyfert-1 galaxy Mrk509
F. Pozo Nunez, N. Gianniotis, J. Blex, T. Lisow, R. Chini, K. L. Polsterer, J.-U. Pott, J. Esser, G. Pietrzy
Monthly Notices of the Royal Astronomical Society, MNRAS, 2019 link
Mixed Variational Inference
Nikolaos Gianniotis
International Joint Conference on Neural Networks, IJCNN, 2019 pdf link
Efficient Optimization of Echo State Networks for Time Series Datasets
Jacob Reinier Maat, Nikos Gianniotis and Pavlos Protopapas
International Joint Conference on Neural Networks, IJCNN, 2018 pdf
Linear Dimensionality Reduction for Time Series
Nikolaos Gianniotis
International Conference on Neural Information Processing, ICONIP, 2017 pdf
A Spectral Model for Multimodal Redshift Estimation
Dennis Kügler, Nikolaos Gianniotis, Kai L. Polsterer
IEEE Symposium on Computational Intelligence and Data Mining, SSCI, 2016 pdf
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs
Kai L. Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis
European Symposium on Artificial Neural Networks, 2016
Model-Coupled Autoencoder for Time Series Visualisation
Nikolaos Gianniotis, Dennis Kügler, Peter Tino, Kai L. Polsterer
Neurocomputing, 2016 pdf link
An Explorative Approach for Inspecting Kepler Data
Dennis Kügler, Nikolaos Gianniotis, Kai L. Polsterer
Monthly Notices of the Royal Astronomical Society Vol. 455, 2015 link
Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables
Nikolaos Gianniotis, Christoph Schnörr, Christian Molkenthin, Sanjay Singh Bora
Pattern Analysis and Applications, Springer, 2015 pdf link
Featureless Classification of Light Curves
Dennis Kügler, Nikolaos Gianniotis, and Kai L. Polsterer
Monthly Notices of the Royal Astronomical Society Vol. 451, 2015 pdf
Autoencoding Time Series for Visualisation
Nikolaos Gianniotis, Dennis Kügler, Peter Tiňo, Kai Polsterer, Ranjeev Misra
European Symposium on Artificial Neural Networks, 2015 pdf
Manifold Aligned Ground Motion Prediction Equations for Regional Datasets
Nikolaos Gianniotis, Nicolas Kühn, Frank Scherbaum
Computers and Geosciences, Elsevier, 2014 link
Interpretable Magnification Factors for Topographic Maps of High Dimensional and Structured Data
Nikolaos Gianniotis
IEEE Symposium on Computational Intelligence and Data Mining, SSCI, 2013 pdf
Visualisation of High-Dimensional Data Using an Ensemble of Neural Networks
Nikolaos Gianniotis, Carsten Riggelsen
IEEE Symposium on Computational Intelligence and Ensemble Learning, SSCI, 2013 pdf
Autoencoding Ground Motion Data for Visualisation
Nikolaos Gianniotis, Carsten Riggelsen, Nicolas Kühn, Frank Scherbaum
International Conference on Artificial Neural Networks, 2012 pdf
Learning Aggregations of Ground Motion Models From Data
Carsten Riggelsen, Nikolaos Gianniotis, Frank Scherbaum
International Conference on Applications of Statistics and Probability in Civil Engineering, 2011
Quantification of Epistemic Uncertainties in Probabilistic Seismic Hazard Analysis
Frank Scherbaum, Nicolas Kuehn, Matthias Ohrnberger, Carsten Riggelsen, Nikolaos Gianniotis
International Conference on Applications of Statistics and Probability in Civil Engineering, 2011
Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model
Nikolaos Gianniotis, Peter Tiňo, Steve Spreckley, Somak Raychaudhury
International Conference on Artificial Neural Networks, 2009 pdf
Visualization of Structured Data via Generative Probabilistic Modeling
Nikolaos Gianniotis, Peter Tiňo
Similarity-Based Clustering, LNAI, 2009 pdf
Visualisation of Tree-Structured Data through Generative Topographic Mapping
Nikolaos Gianniotis, Peter Tiňo
IEEE Transactions on Neural Networks, 2008 pdf
Metric Properties of Structured Data Visualizations through Generative Probabilistic Modeling
Peter Tiňo, Nikolaos Gianniotis
International Joint Conference on Artificial Neural Networks, (IJCAI) 2007 pdf
Visualisation of Tree-structured Data through Generative Probabilistic Modelling
Nikolaos Gianniotis, Peter Tiňo
European Symposium on Artificial Neural Networks, 2007 pdf