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Iván Olier
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2020 – today
- 2024
- [j11]Nosa Aikodon
, Sandra Ortega-Martorell
Predicting Decompensation Risk in Intensive Care Unit Patients Using Machine Learning. Algorithms 17(1): 6 (2024) - 2023
- [j10]Bradley Walters, Sandra Ortega-Martorell
How to Open a Black Box Classifier for Tabular Data. Algorithms 16(4): 181 (2023) - 2022
- [c23]Bradley Walters, Sandra Ortega-Martorell
Towards interpretable machine learning for clinical decision support. IJCNN 2022: 1-8 - 2021
- [c22]Bradley Walters, Sandra Ortega-Martorell
The partial response SVM. ESANN 2021 - 2020
- [c21]Paulo J. G. Lisboa, Sandra Ortega-Martorell
Explaining the Neural Network: A Case Study to Model the Incidence of Cervical Cancer. IPMU (1) 2020: 585-598 - [c20]Paulo J. G. Lisboa, Sandra Ortega-Martorell
Efficient Estimation of General Additive Neural Networks: A Case Study for CTG Data. PKDD/ECML Workshops 2020: 432-446
2010 – 2019
- 2019
- [j9]Noureddin Sadawi
Multi-task learning with a natural metric for quantitative structure activity relationship learning. J. Cheminformatics 11(1): 68:1-68:13 (2019) - [c19]Philippa Grace McCabe
Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis. IDEAL (2) 2019: 114-122 - [c18]Sabrina Marnell
A Comparative Assessment of Feed-Forward and Convolutional Neural Networks for the Classification of Prostate Lesions. IDEAL (2) 2019: 132-138 - [c17]Philippa Grace McCabe
Benchmarking multi-task learning in predictive models for drug discovery. IJCNN 2019: 1-7 - [c16]Patrick Riley
A Voting Ensemble Method to Assist the Diagnosis of Prostate Cancer Using Multiparametric MRI. WSOM+ 2019: 294-303 - [c15]Meenal Srivastava, Iván Olier
Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer. WSOM+ 2019: 304-313 - [i3]Paulo J. G. Lisboa, Sandra Ortega-Martorell, Sadie Cashman, Iván Olier:
The Partial Response Network. CoRR abs/1908.05978 (2019) - 2018
- [j8]Iván Olier
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery. Mach. Learn. 107(1): 285-311 (2018) - [i2]Iván Olier, Oghenejokpeme I. Orhobor, Joaquin Vanschoren, Ross D. King:
Transformative Machine Learning. CoRR abs/1811.03392 (2018) - 2017
- [i1]Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King:
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery. CoRR abs/1709.03854 (2017) - 2015
- [j7]Victor Mocioiu, Sandra Ortega-Martorell
From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML. BMC Bioinform. 16: 378:1-378:11 (2015) - [c14]Iván Olier, Crina Grosan, Noureddin Sadawi, Larisa N. Soldatova, Ross D. King:
Meta-QSAR: Learning How to Learn QSARs. MetaSel@PKDD/ECML 2015: 104-105 - 2014
- [c13]Sandra Ortega-Martorell
Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy. CIDM 2014: 93-98 - [c12]Sandra Ortega-Martorell
Automatic relevance source determination in human brain tumors using Bayesian NMF. CIDM 2014: 99-104 - [c11]Alessandra Tosi, Iván Olier
Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method. WSOM 2014: 55-64 - 2013
- [j6]Iván Olier
A switching multi-scale dynamical network model of EEG/MEG. NeuroImage 83: 262-287 (2013) - 2011
- [j5]Iván Olier
A variational Bayesian approach for the robust analysis of the cortical silent period from EMG recordings of brain stroke patients. Neurocomputing 74(9): 1301-1314 (2011) - [c10]Martha Ivón Cárdenas, Alfredo Vellido
Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree. CIBB 2011: 136-149 - [c9]Alfredo Vellido, Martha Ivón Cárdenas, Iván Olier, Xavier Rovira, Jesús Giraldo:
A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences. ESANN 2011 - 2010
- [j4]Sandra Ortega-Martorell
SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system. BMC Bioinform. 11: 106 (2010) - [j3]Alexander Pérez-Ruiz, Margarida Julià-Sapé, Guillem Mercadal, Iván Olier, Carles Majós, Carles Arús:
The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses. BMC Bioinform. 11: 581 (2010) - [c8]Iván Olier, Julià Amengual, Alfredo Vellido:
Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods. ESANN 2010 - [c7]Iván Olier, Alfredo Vellido, Jesús Giraldo:
Kernel generative topographic mapping. ESANN 2010 - [c6]Sandra Ortega-Martorell, Iván Olier, Alfredo Vellido, Margarida Julià-Sapé, Carles Arús:
Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis. ESANN 2010
2000 – 2009
- 2008
- [j2]Iván Olier
Variational Bayesian Generative Topographic Mapping. J. Math. Model. Algorithms 7(4): 371-387 (2008) - [j1]Iván Olier
Advances in clustering and visualization of time series using GTM through time. Neural Networks 21(7): 904-913 (2008) - [c5]Iván Olier
A variational formulation for GTM through time. IJCNN 2008: 516-521 - [c4]Iván Olier
On the benefits for model regularization of a variational formulation of GTM. IJCNN 2008: 1568-1575 - 2007
- [c3]Iván Olier
Variational GTM. IDEAL 2007: 77-86 - 2006
- [c2]Iván Olier
Time Series Relevance Determination Through a Topology-Constrained Hidden Markov Model. IDEAL 2006: 40-47 - 2005
- [c1]Iván Olier
Comparative Assessment of the Robustness of Missing Data Imputation Through Generative Topographic Mapping. IWANN 2005: 787-794
Coauthor Index
aka: Paulo Lisboa
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last updated on 2024-04-25 05:58 CEST by the dblp team
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