| The variational approximation for Bayesian inference DG Tzikas, AC Likas, NP Galatsanos IEEE Signal Processing Magazine 25 (6), 131-146, 2008 | 947 | 2008 |
| Variational Bayesian sparse kernel-based blind image deconvolution with Student's-t priors DG Tzikas, AC Likas, NP Galatsanos IEEE transactions on image processing 18 (4), 753-764, 2009 | 114 | 2009 |
| Sparse Bayesian modeling with adaptive kernel learning DG Tzikas, AC Likas, NP Galatsanos IEEE Transactions on Neural Networks 20 (6), 926-937, 2009 | 61 | 2009 |
| A tutorial on relevance vector machines for regression and classification with applications DG Tzikas, L Wei, A Likas, Y Yang, NP Galatsanos EURASIP News Letter 17 (2), 4, 2006 | 52 | 2006 |
| Bayesian kernel methods for analysis of functional neuroimages AS Lukic, MN Wernick, DG Tzikas, X Chen, A Likas, NP Galatsanos, ... IEEE Transactions on Medical Imaging 26 (12), 1613-1624, 2007 | 30 | 2007 |
| Variational bayesian blind image deconvolution with student-t priors D Tzikas, A Likas, N Galatsanos 2007 IEEE International Conference on Image Processing 1, I-109-I-112, 2007 | 29 | 2007 |
| Large scale multikernel relevance vector machine for object detection D Tzikas, A Likas, N Galatsanos International Journal on Artificial Intelligence Tools 16 (06), 967-979, 2007 | 14 | 2007 |
| Relevance vector machine analysis of functional neuroimages DG Tzikas, A Likas, NP Galatsanos, AS Lukic, MN Wernick 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro …, 2004 | 14 | 2004 |
| Large scale multikernel RVM for object detection D Tzikas, A Likas, N Galatsanos Hellenic Conference on Artificial Intelligence, 389-399, 2006 | 13 | 2006 |
| Incremental relevance vector machine with kernel learning D Tzikas, A Likas, N Galatsanos Hellenic Conference on Artificial Intelligence, 301-312, 2008 | 11 | 2008 |
| An incremental bayesian approach for training multilayer perceptrons D Tzikas, A Likas International Conference on Artificial Neural Networks, 87-96, 2010 | 9 | 2010 |
| Transductive reliability estimation for kernel based classifiers D Tzikas, M Kukar, A Likas International Symposium on Intelligent Data Analysis, 37-47, 2007 | 6 | 2007 |
| Bayesian regression of functional neuroimages DG Tzikas, A Likas, NP Galatsanos, AS Lukic, MN Wernick 2004 12th European Signal Processing Conference, 801-804, 2004 | 6 | 2004 |
| Local feature selection for the relevance vector machine using adaptive kernel learning D Tzikas, A Likas, N Galatsanos Artificial Neural Networks–ICANN 2009: 19th International Conference …, 2009 | 4 | 2009 |
| Robust variational bayesian kernel based blind image deconvolution. D Tzikas, A Likas, NP Galatsanos VISAPP (Special Sessions), 143-150, 2007 | 2 | 2007 |
| Variational Bayesian blind image deconvolution based on a sparse kernel model for the point spread function D Tzikas, A Likas, N Galatsanos 2006 14th European Signal Processing Conference, 1-5, 2006 | 2 | 2006 |
| Life After the EM Algorithm: The Variational Approximation for Bayesian Inference D Tzikas, A Likas, N Galatsanos IEEE Signal Processing Magazine 25 (6), 0 | 2 | |
| Bayesian bid based on a kernel model for the point spread function D Tzikas, A Likas, N Galatsanos Proceedings of International Conference on Image Processing, 0 | 1 | |
| Kernel Methods for Functional Neuroimaging Analysis AS Lukic, MN Wernick, DG Tzikas, X Chen, A Likas, NP Galatsanos, ... 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 161-165, 2006 | | 2006 |
| Local Feature Selection using Adaptive Kernel Learning for the Relevance Vector Machine D Tzikas, A Likas, N Galatsanos | | |
