Fast feature selection using a simple estimation of distribution algorithm: a case study on splice site prediction. - Yvan Saeys; Sven Degroeve; Dirk Aeyels; Yves Van de Peer; Pierre Rouzé (ECCB, 2003)

Digging into Acceptor Splice Site Prediction: An Iterative Feature Selection Approach. - Yvan Saeys; Sven Degroeve; Yves Van de Peer (PKDD, 2004)

Feature selection for splice site prediction: A new method using EDA-based feature ranking. - Yvan Saeys; Sven Degroeve; Dirk Aeyels; Pierre Rouzé; Yves Van de Peer (BMC Bioinform., 2004)

SpliceMachine: predicting splice sites from high-dimensional local context representations. - Sven Degroeve; Yvan Saeys; Bernard De Baets; Pierre Rouzé; Yves Van de Peer (Bioinform., 2005)

Feature Ranking Using an EDA-based Wrapper Approach. - Yvan Saeys; Sven Degroeve; Yves Van de Peer (Towards a New Evolutionary Computation, 2006)

Feature Extraction Using Clustering of Protein. - Isis Bonet; Yvan Saeys; Ricardo Grau Ábalo; María M. García; Robersy Sanchez; Yves Van de Peer (CIARP, 2006)

Scalable hardware accelerator for comparing DNA and protein sequences. - Philippe Faes; Bram Minnaert; Mark Christiaens; Eric Bonnet; Yvan Saeys; Dirk Stroobandt; Yves Van de Peer (Infoscale, 2006)

Enhancing Coding Potential Prediction for Short Sequences Using Complementary Sequence Features and Feature Selection. - Yvan Saeys; Yves Van de Peer (KDECB, 2006)

Knowledge Discovery and Emergent Complexity in Bioinformatics. - Ronald L. Westra; Karl Tuyls; Yvan Saeys; Ann Nowé (KDECB, 2006)

Translation initiation site prediction on a genomic scale: beauty in simplicity. - Yvan Saeys; Thomas Abeel; Sven Degroeve; Yves Van de Peer (ISMB/ECCB (Supplement of Bioinformatics), 2007)

Predicting Human Immunodeficiency Virus (HIV) Drug Resistance Using Recurrent Neural Networks. - Isis Bonet; María M. García; Yvan Saeys; Yves Van de Peer; Ricardo Grau Ábalo (IWINAC (1), 2007)

A review of feature selection techniques in bioinformatics. - Yvan Saeys; Iñaki Inza; Pedro Larrañaga (Bioinform., 2007)

In search of the small ones: improved prediction of short exons in vertebrates, plants, fungi and protists. - Yvan Saeys; Pierre Rouzé; Yves Van de Peer (Bioinform., 2007)

Validating module network learning algorithms using simulated data. - Tom Michoel; Steven Maere; Eric Bonnet; Anagha Joshi; Yvan Saeys; Tim Van den Bulcke; Koenraad Van Leemput; Piet van Remortel; Martin Kuiper; Kathleen Marchal; Yves Van de Peer (BMC Bioinform., 2007)

ProSOM: core promoter prediction based on unsupervised clustering of DNA physical profiles. - Thomas Abeel; Yvan Saeys; Pierre Rouzé; Yves Van de Peer (ISMB, 2008)

Comparing Distance Measures with Visual Methods. - Isis Bonet; Abdel Rodríguez; Ricardo Grau Ábalo; María M. García; Yvan Saeys; Ann Nowé (MICAI, 2008)

Robust Feature Selection Using Ensemble Feature Selection Techniques. - Yvan Saeys; Thomas Abeel; Yves Van de Peer (ECML/PKDD (2), 2008)

A review of estimation of distribution algorithms in bioinformatics. - Rubén Armañanzas; Iñaki Inza; Roberto Santana 001; Yvan Saeys; Jose Luis Flores 001; José Antonio Lozano 001; Yves Van de Peer; Rosa Blanco; Víctor Robles; Concha Bielza; Pedro Larrañaga (BioData Min., 2008)

FunSiP: a modular and extensible classifier for the prediction of functional sites in DNA. - Michiel Van Bel; Yvan Saeys; Yves Van de Peer (Bioinform., 2008)

Preface. - Yvan Saeys; Huan Liu; Iñaki Inza; Louis Wehenkel; Yves Van de Peer (FSDM, 2008)

Analyzing text in search of bio-molecular events: a high-precision machine learning framework. - Sofie Van Landeghem; Yvan Saeys; Bernard De Baets; Yves Van de Peer (BioNLP@HLT-NAACL (Shared Task), 2009)

Valued Constraint Satisfaction Problems Applied to Functional Harmony. - Nele Verbiest; Chris Cornelis; Yvan Saeys (IFSA/EUSFLAT Conf., 2009)

Toward a gold standard for promoter prediction evaluation. - Thomas Abeel; Yves Van de Peer; Yvan Saeys (Bioinform., 2009)

Java-ML: A Machine Learning Library. - Thomas Abeel; Yves Van de Peer; Yvan Saeys (J. Mach. Learn. Res., 2009)

Towards an ASR-free objective analysis of pathological speech. - Catherine Middag; Yvan Saeys; Jean-Pierre Martens (INTERSPEECH, 2010)

Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. - Thomas Abeel; Thibault Helleputte; Yves Van de Peer; Pierre Dupont; Yvan Saeys (Bioinform., 2010)

Discriminative and informative features for biomolecular text mining with ensemble feature selection. - Sofie Van Landeghem; Thomas Abeel; Yvan Saeys; Yves Van de Peer (Bioinform., 2010)

Highlights of the BioTM 2010 workshop on advances in bio text mining. - Thomas Abeel; Sofie Van Landeghem; Roser Morante; Vincent Van Asch; Yves Van de Peer; Walter Daelemans; Yvan Saeys (BMC Bioinform., 2010)

Event based text mining for integrated network construction. - Yvan Saeys; Sofie Van Landeghem; Yves Van de Peer (MLSB, 2010)

An alternative approach to avoid overfitting for surrogate models. - Huu Minh Nguyen; Ivo Couckuyt; Luc Knockaert; Tom Dhaene; Dirk Gorissen; Yvan Saeys (WSC, 2011)

A greedy, graph-based algorithm for the alignment of multiple homologous gene lists. - Jan Fostier; Sebastian Proost; Bart Dhoedt; Yvan Saeys; Piet Demeester; Yves Van de Peer; Klaas Vandepoele (Bioinform., 2011)

High-Precision Bio-molecular Event Extraction from Text Using Parallel Binary Classifiers. - Sofie Van Landeghem; Bernard De Baets; Yves Van de Peer; Yvan Saeys (Comput. Intell., 2011)

Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms. - Rubén Armañanzas; Yvan Saeys; Iñaki Inza; Miguel García-Torres; Concha Bielza; Yves Van de Peer; Pedro Larrañaga (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

SBFC: An Efficient Feature Frequency-Based Approach to Tackle Cross-Lingual Word Sense Disambiguation. - Dieter Mourisse; Els Lefever; Nele Verbiest; Yvan Saeys; Martine De Cock; Chris Cornelis (TSD, 2012)

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. - Vân Anh Huynh-Thu; Yvan Saeys; Louis Wehenkel; Pierre Geurts (Bioinform., 2012)

Complex Aggregates over Clusters of Elements. - Celine Vens; Sofie Van Gassen; Tom Dhaene; Yvan Saeys (ILP, 2014)

Noise Analysis and Removal in 3D Electron Microscopy. - Joris Roels; Jan Aelterman; Jonas De Vylder; Hiêp Quang Luong; Yvan Saeys; Saskia Lippens; Wilfried Philips (ISVC (1), 2014)

Evolutionary undersampling for imbalanced big data classification. - Isaac Triguero; Mikel Galar; Sarah Vluymans; Chris Cornelis; Humberto Bustince; Francisco Herrera; Yvan Saeys (CEC, 2015)

Unsupervised Trajectory Inference Using Graph Mining. - Leen De Baets; Sofie Van Gassen; Tom Dhaene; Yvan Saeys (CIBB, 2015)

Fuzzy Rough Set Prototype Selection for Regression. - Sarah Vluymans; Yvan Saeys; Chris Cornelis; Ankur Teredesai; Martine De Cock (FUZZ-IEEE, 2015)

Distributed fuzzy rough prototype selection for Big Data regression. - Sarah Vluymans; Hasan Asfoor; Yvan Saeys; Chris Cornelis; Matthew E. Tolentino; Ankur Teredesai; Martine De Cock (NAFIPS/WConSC, 2015)

Semi-Supervised Fuzzy-Rough Feature Selection. - Richard Jensen; Sarah Vluymans; Neil Mac Parthaláin; Chris Cornelis; Yvan Saeys (RSFDGrC, 2015)

Applications of Fuzzy Rough Set Theory in Machine Learning: a Survey. - Sarah Vluymans; Lynn D'eer; Yvan Saeys; Chris Cornelis (Fundam. Informaticae, 2015)

Decreasing Time Consumption of Microscopy Image Segmentation Through Parallel Processing on the GPU. - Joris Roels; Jonas De Vylder; Yvan Saeys; Bart Goossens; Wilfried Philips (ACIVS, 2016)

Bayesian deconvolution of scanning electron microscopy images using point-spread function estimation and non-local regularization. - Joris Roels; Jan Aelterman; Jonas De Vylder; Hiêp Quang Luong; Yvan Saeys; Wilfried Philips (EMBC, 2016)

Fuzzy rough sets for self-labelling: An exploratory analysis. - Sarah Vluymans; Neil Mac Parthaláin; Chris Cornelis; Yvan Saeys (FUZZ-IEEE, 2016)

Machine Learning Challenges for Single Cell Data. - Sofie Van Gassen; Tom Dhaene; Yvan Saeys (ECML/PKDD (3), 2016)

Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets. - Nele Verbiest; Sarah Vluymans; Chris Cornelis; Nicolás García-Pedrajas; Yvan Saeys (Appl. Soft Comput., 2016)

Netter: re-ranking gene network inference predictions using structural network properties. - Joeri Ruyssinck; Piet Demeester; Tom Dhaene; Yvan Saeys (BMC Bioinform., 2016)

EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data. - Sarah Vluymans; Isaac Triguero; Chris Cornelis; Yvan Saeys (Neurocomputing, 2016)

Fuzzy rough classifiers for class imbalanced multi-instance data. - Sarah Vluymans; Dánel Sánchez Tarragó; Yvan Saeys; Chris Cornelis; Francisco Herrera (Pattern Recognit., 2016)

Fuzzy Multi-Instance Classifiers. - Sarah Vluymans; Dánel Sánchez Tarragó; Yvan Saeys; Chris Cornelis; Francisco Herrera (IEEE Trans. Fuzzy Syst., 2016)

Interpretable convolutional neural networks for effective translation initiation site prediction. - Jasper Zuallaert; Mijung Kim; Yvan Saeys; Wesley De Neve (BIBM, 2017)

Convolutional neural network pruning to accelerate membrane segmentation in electron microscopy. - Joris Roels; Jonas De Vylder; Jan Aelterman; Yvan Saeys; Wilfried Philips (ISBI, 2017)

Lower bounds on the robustness to adversarial perturbations. - Jonathan Peck; Joris Roels; Bart Goossens; Yvan Saeys (NIPS, 2017)

Fingerprint classification with a new deep neural network model: robustness for different captures of the same fingerprints. - Daniel Peralta; Isaac Triguero; Salvador García 001; Yvan Saeys; José Manuel Benítez 001; Francisco Herrera (CoRR, 2017)

Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection. - Daniel Peralta; Isaac Triguero; Salvador García 001; Yvan Saeys; José Manuel Benítez 001; Francisco Herrera (Knowl. Based Syst., 2017)

ConTra v3: a tool to identify transcription factor binding sites across species, update 2017. - Lukasz Kreft; Arne Soete; Paco Hulpiau; Alexander Botzki; Yvan Saeys; Pieter J. De Bleser (Nucleic Acids Res., 2017)

Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies. - Robin Vandaele; Tijl De Bie; Yvan Saeys (ECML/PKDD (2), 2018)

SpliceRover: interpretable convolutional neural networks for improved splice site prediction. - Jasper Zuallaert; Fréderic Godin; Mijung Kim; Arne Soete; Yvan Saeys; Wesley De Neve (Bioinform., 2018)

TISRover: ConvNets learn biologically relevant features for effective translation initiation site prediction. - Jasper Zuallaert; Mijung Kim; Arne Soete; Yvan Saeys; Wesley De Neve (Int. J. Data Min. Bioinform., 2018)

On the use of convolutional neural networks for robust classification of multiple fingerprint captures. - Daniel Peralta; Isaac Triguero; Salvador García 001; Yvan Saeys; José Manuel Benítez 001; Francisco Herrera (Int. J. Intell. Syst., 2018)

Multi-label classification using a fuzzy rough neighborhood consensus. - Sarah Vluymans; Chris Cornelis; Francisco Herrera; Yvan Saeys (Inf. Sci., 2018)

Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach. - Sarah Vluymans; Alberto Fernández 001; Yvan Saeys; Chris Cornelis; Francisco Herrera (Knowl. Inf. Syst., 2018)

Distributed, Numerically Stable Distance and Covariance Computation with MPI for Extremely Large Datasets. - Daniel Peralta; Yvan Saeys (BigData Congress, 2019)

Distillation of Deep Reinforcement Learning Models Using Fuzzy Inference Systems. - Arne Gevaert; Jonathan Peck; Yvan Saeys (BNAIC/BENELEARN, 2019)

Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry. - Maxim Lippeveld; Carly Knill; Emma Ladlow; Andrew Fuller; Louise J. Michaelis; Yvan Saeys; Andrew Filby; Daniel Peralta (BNAIC/BENELEARN, 2019)

Calibrated Multi-probabilistic Prediction as a Defense Against Adversarial Attacks. - Jonathan Peck; Bart Goossens; Yvan Saeys (BNAIC/BENELEARN (Selected Papers), 2019)

Cost-Efficient Segmentation of Electron Microscopy Images Using Active Learning. - Joris Roels; Yvan Saeys (BNAIC/BENELEARN, 2019)

Detecting adversarial examples with inductive Venn-ABERS predictors. - Jonathan Peck; Bart Goossens; Yvan Saeys (ESANN, 2019)

Domain Adaptive Segmentation In Volume Electron Microscopy Imaging. - Joris Roels; Julian Hennies; Yvan Saeys; Wilfried Philips; Anna Kreshuk (ISBI, 2019)

Weight selection strategies for ordered weighted average based fuzzy rough sets. - Sarah Vluymans; Neil Mac Parthaláin; Chris Cornelis; Yvan Saeys (Inf. Sci., 2019)

Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph. - Pieter Meysman; Yvan Saeys; Ehsan Sabaghian; Wout Bittremieux; Yves Van de Peer; Bart Goethals; Kris Laukens (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Graph Approximations to Geodesics on Metric Graphs. - Robin Vandaele; Yvan Saeys; Tijl De Bie (ICPR, 2020)

Asynchronous Processing for Latent Fingerprint Identification on Heterogeneous CPU-GPU Systems. - Andres Jesus Sanchez; Luis F. Romero; Daniel Peralta; Miguel Angel Medina-Pérez; Yvan Saeys; Francisco Herrera; Siham Tabik (IEEE Access, 2020)

Robust unsupervised dimensionality reduction based on feature clustering for single-cell imaging data. - Daniel Peralta; Yvan Saeys (Appl. Soft Comput., 2020)

TinGa: fast and flexible trajectory inference with Growing Neural Gas. - Helena Todorov; Robrecht Cannoodt; Wouter Saelens; Yvan Saeys (Bioinform., 2020)

Regional Image Perturbation Reduces Lp Norms of Adversarial Examples While Maintaining Model-to-model Transferability. - Utku Ozbulak; Jonathan Peck; Wesley De Neve; Bart Goossens; Yvan Saeys; Arnout Van Messem (CoRR, 2020)

Detecting adversarial manipulation using inductive Venn-ABERS predictors. - Jonathan Peck; Bart Goossens; Yvan Saeys (Neurocomputing, 2020)

Mining Topological Structure in Graphs through Forest Representations. - Robin Vandaele; Yvan Saeys; Tijl De Bie (J. Mach. Learn. Res., 2020)

A study on the calibration of fingerprint classifiers. - Daniel Peralta; Lin Tang; Maxim Lippeveld; Yvan Saeys (IEEE BigData, 2021)

The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data. - Robin Vandaele; Bo Kang; Tijl De Bie; Yvan Saeys (CoRR, 2021)

SCMFTS: Scalable and Distributed Complexity Measures and Features for Univariate and Multivariate Time Series in Big Data Environments. - Francisco Javier Baldan; Daniel Peralta; Yvan Saeys; José Manuel Benítez 001 (Int. J. Comput. Intell. Syst., 2021)

Stable topological signatures for metric trees through graph approximations. - Robin Vandaele; Bastian Rieck; Yvan Saeys; Tijl De Bie (Pattern Recognit. Lett., 2021)

The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data? - Robin Vandaele; Bo Kang; Tijl De Bie; Yvan Saeys (AISTATS, 2022)

Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems. - Arne Gevaert; Jonathan Peck; Yvan Saeys (FUZZ-IEEE, 2022)

Topologically Regularized Data Embeddings. - Robin Vandaele; Bo Kang; Jefrey Lijffijt; Tijl De Bie; Yvan Saeys (ICLR, 2022)

BioSegment: Active Learning segmentation for 3D electron microscopy imaging. - Benjamin Rombaut 001; Joris Roels; Yvan Saeys (IAL@PKDD/ECML, 2022)

PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition. - Arne Gevaert; Yvan Saeys (CoRR, 2022)

Evaluating Feature Attribution Methods in the Image Domain: Benchmark results and model parameters. - Arne Gevaert; Axel-Jan Rousseau; Thijs Becker; Dirk Valkenborg; Tijl De Bie; Yvan Saeys (Zenodo, 2022)

Evaluating Feature Attribution Methods in the Image Domain: High-Dimensional Datasets. - Arne Gevaert; Axel-Jan Rousseau; Thijs Becker; Dirk Valkenborg; Tijl De Bie; Yvan Saeys (Zenodo, 2022)

Efficient Approximation of Asymmetric Shapley Values Using Functional Decomposition. - Arne Gevaert; Anna Saranti; Andreas Holzinger; Yvan Saeys (CD-MAKE, 2023)

Topologically Regularized Data Embeddings. - Edith Heiter; Robin Vandaele; Tijl De Bie; Yvan Saeys; Jefrey Lijffijt (CoRR, 2023)

GroupEnc: encoder with group loss for global structure preservation. - David Novak; Sofie Van Gassen; Yvan Saeys (CoRR, 2023)

Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. - Edith Heiter; Liesbet Martens; Ruth Seurinck; Martin Guilliams; Tijl De Bie; Yvan Saeys; Jefrey Lijffijt (ECML/PKDD (8), 2024)

Incorporating Topological Priors Into Low-Dimensional Visualizations Through Topological Regularization. - Edith Heiter; Robin Vandaele; Tijl De Bie; Yvan Saeys; Jefrey Lijffijt (IEEE Access, 2024)

Unifying Attribution-Based Explanations Using Functional Decomposition. - Arne Gevaert; Yvan Saeys (CoRR, 2024)

Evaluating Feature Attribution Methods in the Image Domain: Benchmark results and model parameters. - Arne Gevaert; Axel-Jan Rousseau; Thijs Becker; Dirk Valkenborg; Tijl De Bie; Yvan Saeys (Zenodo, 2024)

An Introduction to Adversarially Robust Deep Learning. - Jonathan Peck; Bart Goossens; Yvan Saeys (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Evaluating feature attribution methods in the image domain. - Arne Gevaert; Axel-Jan Rousseau; Thijs Becker; Dirk Valkenborg; Tijl De Bie; Yvan Saeys (Mach. Learn., 2024)

Evaluation of out-of-distribution detection methods for data shifts in single-cell transcriptomics. - Lauren Theunissen; Thomas Mortier; Yvan Saeys; Willem Waegeman (Briefings Bioinform., 2025)

Feature Subset Weighting for Distance-based Supervised Learning through Choquet Integration. - Adnan Theerens; Yvan Saeys; Chris Cornelis (CoRR, 2025)

funkyheatmap: Visualising data frames with mixed data types. - Robrecht Cannoodt; Louise Deconinck; Artuur Couckuyt; Nikolay S. Markov; Luke Zappia; Malte D. Lücken; Marta Interlandi; Yvan Saeys; Wouter Saelens (J. Open Source Softw., 2025)