Yvan Saeys

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 67

Top Venues

Publications

Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. CoRR (2024)
Jonathan Peck, Bart Goossens, Yvan Saeys
An Introduction to Adversarially Robust Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46 (4) (2024)
Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys
Evaluating feature attribution methods in the image domain. Mach. Learn. 113 (9) (2024)
Arne Gevaert, Anna Saranti, Andreas Holzinger, Yvan Saeys
Efficient Approximation of Asymmetric Shapley Values Using Functional Decomposition. CD-MAKE (2023)
David Novak, Sofie Van Gassen, Yvan Saeys
GroupEnc: encoder with group loss for global structure preservation. CoRR (2023)
Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
Topologically Regularized Data Embeddings. CoRR (2023)
Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
Topologically Regularized Data Embeddings. ICLR (2022)
Benjamin Rombaut, Joris Roels, Yvan Saeys
BioSegment: Active Learning segmentation for 3D electron microscopy imaging. IAL@PKDD/ECML (2022)
Arne Gevaert, Jonathan Peck, Yvan Saeys
Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems. FUZZ-IEEE (2022)
Arne Gevaert, Jonathan Peck, Yvan Saeys
Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems. CoRR (2022)
Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data? AISTATS (2022)
Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys
Evaluating Feature Attribution Methods in the Image Domain. CoRR (2022)
Arne Gevaert, Yvan Saeys
PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition. CoRR (2022)
Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
Topologically Regularized Data Embeddings. CoRR (2021)
Francisco Javier Baldan, Daniel Peralta, Yvan Saeys, José Manuel Benítez
SCMFTS: Scalable and Distributed Complexity Measures and Features for Univariate and Multivariate Time Series in Big Data Environments. Int. J. Comput. Intell. Syst. 14 (1) (2021)
Robin Vandaele, Bastian Rieck, Yvan Saeys, Tijl De Bie
Stable topological signatures for metric trees through graph approximations. Pattern Recognit. Lett. 147 (2021)
Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys
The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data. CoRR (2021)
Daniel Peralta, Lin Tang, Maxim Lippeveld, Yvan Saeys
A study on the calibration of fingerprint classifiers. IEEE BigData (2021)
Daniel Peralta, Yvan Saeys
Robust unsupervised dimensionality reduction based on feature clustering for single-cell imaging data. Appl. Soft Comput. 93 (2020)
Helena Todorov, Robrecht Cannoodt, Wouter Saelens, Yvan Saeys
TinGa: fast and flexible trajectory inference with Growing Neural Gas. Bioinform. 36 (Supplement-1) (2020)
Utku Ozbulak, Jonathan Peck, Wesley De Neve, Bart Goossens, Yvan Saeys, Arnout Van Messem
Norms of Adversarial Examples While Maintaining Model-to-model Transferability. CoRR (2020)
Andres Jesus Sanchez, Luis F. Romero, Daniel Peralta, Miguel Angel Medina-Pérez, Yvan Saeys, Francisco Herrera, Siham Tabik
Asynchronous Processing for Latent Fingerprint Identification on Heterogeneous CPU-GPU Systems. IEEE Access 8 (2020)
Robin Vandaele, Yvan Saeys, Tijl De Bie
Graph Approximations to Geodesics on Metric Graphs. ICPR (2020)
Robin Vandaele, Yvan Saeys, Tijl De Bie
Mining Topological Structure in Graphs through Forest Representations. J. Mach. Learn. Res. 21 (2020)
Jonathan Peck, Bart Goossens, Yvan Saeys
Detecting adversarial manipulation using inductive Venn-ABERS predictors. Neurocomputing 416 (2020)
Pieter Meysman, Yvan Saeys, Ehsan Sabaghian, Wout Bittremieux, Yves Van de Peer, Bart Goethals, Kris Laukens
Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (5) (2019)
Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys
Weight selection strategies for ordered weighted average based fuzzy rough sets. Inf. Sci. 501 (2019)
Maxim Lippeveld, Carly Knill, Emma Ladlow, Andrew Fuller, Louise J. Michaelis, Yvan Saeys, Andrew Filby, Daniel Peralta
Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry. BNAIC/BENELEARN (2019)
Jonathan Peck, Bart Goossens, Yvan Saeys
Detecting adversarial examples with inductive Venn-ABERS predictors. ESANN (2019)
Jonathan Peck, Bart Goossens, Yvan Saeys
Calibrated Multi-probabilistic Prediction as a Defense Against Adversarial Attacks. BNAIC/BENELEARN (Selected Papers) (2019)
Joris Roels, Julian Hennies, Yvan Saeys, Wilfried Philips, Anna Kreshuk
Domain Adaptive Segmentation In Volume Electron Microscopy Imaging. ISBI (2019)
Joris Roels, Yvan Saeys
Cost-efficient segmentation of electron microscopy images using active learning. CoRR (2019)
Arne Gevaert, Jonathan Peck, Yvan Saeys
Distillation of Deep Reinforcement Learning Models Using Fuzzy Inference Systems. BNAIC/BENELEARN (2019)
Joris Roels, Yvan Saeys
Cost-Efficient Segmentation of Electron Microscopy Images Using Active Learning. BNAIC/BENELEARN (2019)
Jonathan Peck, Bart Goossens, Yvan Saeys
Calibrated Multi-Probabilistic Prediction as a Defense against Adversarial Attacks. BNAIC/BENELEARN (2019)
Daniel Peralta, Yvan Saeys
Distributed, Numerically Stable Distance and Covariance Computation with MPI for Extremely Large Datasets. BigData Congress (2019)
Joris Roels, Jonas De Vylder, Jan Aelterman, Yvan Saeys, Wilfried Philips
Convolutional Neural Network Pruning to Accelerate Membrane Segmentation in Electron Microscopy. CoRR (2018)
Joris Roels, Julian Hennies, Yvan Saeys, Wilfried Philips, Anna Kreshuk
Domain Adaptive Segmentation in Volume Electron Microscopy Imaging. CoRR (2018)
Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera
On the use of convolutional neural networks for robust classification of multiple fingerprint captures. Int. J. Intell. Syst. 33 (1) (2018)
Sarah Vluymans, Alberto Fernández, Yvan Saeys, Chris Cornelis, Francisco Herrera
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach. Knowl. Inf. Syst. 56 (1) (2018)
Robin Vandaele, Tijl De Bie, Yvan Saeys
Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies. ECML/PKDD (2) (2018)
Joris Roels, Jan Aelterman, Jonas De Vylder, Hiêp Quang Luong, Yvan Saeys, Wilfried Philips
Bayesian Deconvolution of Scanning Electron Microscopy Images Using Point-spread Function Estimation and Non-local Regularization. CoRR (2018)
Sarah Vluymans, Chris Cornelis, Francisco Herrera, Yvan Saeys
Multi-label classification using a fuzzy rough neighborhood consensus. Inf. Sci. (2018)
Jasper Zuallaert, Fréderic Godin, Mijung Kim, Arne Soete, Yvan Saeys, Wesley De Neve
SpliceRover: interpretable convolutional neural networks for improved splice site prediction. Bioinform. 34 (24) (2018)
Jasper Zuallaert, Mijung Kim, Arne Soete, Yvan Saeys, Wesley De Neve
TISRover: ConvNets learn biologically relevant features for effective translation initiation site prediction. Int. J. Data Min. Bioinform. 20 (3) (2018)
Joris Roels, Jonas De Vylder, Jan Aelterman, Yvan Saeys, Wilfried Philips
Convolutional neural network pruning to accelerate membrane segmentation in electron microscopy. ISBI (2017)
Jasper Zuallaert, Mijung Kim, Yvan Saeys, Wesley De Neve
Interpretable convolutional neural networks for effective translation initiation site prediction. BIBM (2017)
Jonathan Peck, Joris Roels, Bart Goossens, Yvan Saeys
Lower bounds on the robustness to adversarial perturbations. NIPS (2017)
Jasper Zuallaert, Mijung Kim, Yvan Saeys, Wesley De Neve
Interpretable Convolutional Neural Networks for Effective Translation Initiation Site Prediction. CoRR (2017)
Lukasz Kreft, Arne Soete, Paco Hulpiau, Alexander Botzki, Yvan Saeys, Pieter J. De Bleser
ConTra v3: a tool to identify transcription factor binding sites across species, update 2017. Nucleic Acids Res. 45 (Webserver-Issue) (2017)
Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera
Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection. Knowl. Based Syst. 126 (2017)
Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera
Fingerprint classification with a new deep neural network model: robustness for different captures of the same fingerprints. CoRR (2017)
Joeri Ruyssinck, Piet Demeester, Tom Dhaene, Yvan Saeys
Netter: re-ranking gene network inference predictions using structural network properties. BMC Bioinform. 17 (2016)
Joris Roels, Jan Aelterman, Jonas De Vylder, Hiêp Quang Luong, Yvan Saeys, Wilfried Philips
Bayesian deconvolution of scanning electron microscopy images using point-spread function estimation and non-local regularization. EMBC (2016)
Sarah Vluymans, Isaac Triguero, Chris Cornelis, Yvan Saeys
EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data. Neurocomputing 216 (2016)
Joris Roels, Jonas De Vylder, Yvan Saeys, Bart Goossens, Wilfried Philips
Decreasing Time Consumption of Microscopy Image Segmentation Through Parallel Processing on the GPU. ACIVS (2016)
Nele Verbiest, Sarah Vluymans, Chris Cornelis, Nicolás García-Pedrajas, Yvan Saeys
Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets. Appl. Soft Comput. 44 (2016)
Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys
Fuzzy rough sets for self-labelling: An exploratory analysis. FUZZ-IEEE (2016)
Sofie Van Gassen, Tom Dhaene, Yvan Saeys
Machine Learning Challenges for Single Cell Data. ECML/PKDD (3) (2016)
Sarah Vluymans, Dánel Sánchez Tarragó, Yvan Saeys, Chris Cornelis, Francisco Herrera
Fuzzy Multi-Instance Classifiers. IEEE Trans. Fuzzy Syst. 24 (6) (2016)
Sarah Vluymans, Dánel Sánchez Tarragó, Yvan Saeys, Chris Cornelis, Francisco Herrera
Fuzzy rough classifiers for class imbalanced multi-instance data. Pattern Recognit. 53 (2016)
Isaac Triguero, Mikel Galar, Sarah Vluymans, Chris Cornelis, Humberto Bustince, Francisco Herrera, Yvan Saeys
Evolutionary undersampling for imbalanced big data classification. CEC (2015)
Sarah Vluymans, Lynn D'eer, Yvan Saeys, Chris Cornelis
Applications of Fuzzy Rough Set Theory in Machine Learning: a Survey. Fundam. Informaticae 142 (1-4) (2015)
Richard Jensen, Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys
Semi-Supervised Fuzzy-Rough Feature Selection. RSFDGrC (2015)
Sarah Vluymans, Hasan Asfoor, Yvan Saeys, Chris Cornelis, Matthew E. Tolentino, Ankur Teredesai, Martine De Cock
Distributed fuzzy rough prototype selection for Big Data regression. NAFIPS/WConSC (2015)
Sarah Vluymans, Yvan Saeys, Chris Cornelis, Ankur Teredesai, Martine De Cock
Fuzzy Rough Set Prototype Selection for Regression. FUZZ-IEEE (2015)
Leen De Baets, Sofie Van Gassen, Tom Dhaene, Yvan Saeys
Unsupervised Trajectory Inference Using Graph Mining. CIBB (2015)
Joris Roels, Jan Aelterman, Jonas De Vylder, Hiêp Quang Luong, Yvan Saeys, Saskia Lippens, Wilfried Philips
Noise Analysis and Removal in 3D Electron Microscopy. ISVC (1) (2014)
Celine Vens, Sofie Van Gassen, Tom Dhaene, Yvan Saeys
Complex Aggregates over Clusters of Elements. ILP (2014)
Dieter Mourisse, Els Lefever, Nele Verbiest, Yvan Saeys, Martine De Cock, Chris Cornelis
SBFC: An Efficient Feature Frequency-Based Approach to Tackle Cross-Lingual Word Sense Disambiguation. TSD (2012)
Vân Anh Huynh-Thu, Yvan Saeys, Louis Wehenkel, Pierre Geurts
Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. Bioinform. 28 (13) (2012)
Rubén Armañanzas, Yvan Saeys, Iñaki Inza, Miguel García-Torres, Concha Bielza, Yves Van de Peer, Pedro Larrañaga
Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms. IEEE ACM Trans. Comput. Biol. Bioinform. 8 (3) (2011)
Huu Minh Nguyen, Ivo Couckuyt, Luc Knockaert, Tom Dhaene, Dirk Gorissen, Yvan Saeys
An alternative approach to avoid overfitting for surrogate models. WSC (2011)
Sofie Van Landeghem, Bernard De Baets, Yves Van de Peer, Yvan Saeys
High-Precision Bio-molecular Event Extraction from Text Using Parallel Binary Classifiers. Comput. Intell. 27 (4) (2011)
Jan Fostier, Sebastian Proost, Bart Dhoedt, Yvan Saeys, Piet Demeester, Yves Van de Peer, Klaas Vandepoele
A greedy, graph-based algorithm for the alignment of multiple homologous gene lists. Bioinform. 27 (6) (2011)
Thomas Abeel, Sofie Van Landeghem, Roser Morante, Vincent Van Asch, Yves Van de Peer, Walter Daelemans, Yvan Saeys
Highlights of the BioTM 2010 workshop on advances in bio text mining. BMC Bioinform. 11 (S-5) (2010)
Thomas Abeel, Thibault Helleputte, Yves Van de Peer, Pierre Dupont, Yvan Saeys
Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. Bioinform. 26 (3) (2010)
Yvan Saeys, Sofie Van Landeghem, Yves Van de Peer
Event based text mining for integrated network construction. MLSB (2010)
Catherine Middag, Yvan Saeys, Jean-Pierre Martens
Towards an ASR-free objective analysis of pathological speech. INTERSPEECH (2010)
Sofie Van Landeghem, Thomas Abeel, Yvan Saeys, Yves Van de Peer
Discriminative and informative features for biomolecular text mining with ensemble feature selection. Bioinform. 26 (18) (2010)
Thomas Abeel, Yves Van de Peer, Yvan Saeys
Toward a gold standard for promoter prediction evaluation. Bioinform. 25 (12) (2009)
Sofie Van Landeghem, Yvan Saeys, Bernard De Baets, Yves Van de Peer
Analyzing text in search of bio-molecular events: a high-precision machine learning framework. BioNLP@HLT-NAACL (Shared Task) (2009)
Thomas Abeel, Yves Van de Peer, Yvan Saeys
Java-ML: A Machine Learning Library. J. Mach. Learn. Res. 10 (2009)
Nele Verbiest, Chris Cornelis, Yvan Saeys
Valued Constraint Satisfaction Problems Applied to Functional Harmony. IFSA/EUSFLAT Conf. (2009)
Isis Bonet, Abdel Rodríguez, Ricardo Grau Ábalo, María M. García, Yvan Saeys, Ann Nowé
Comparing Distance Measures with Visual Methods. MICAI (2008)
Yvan Saeys, Huan Liu, Iñaki Inza, Louis Wehenkel, Yves Van de Peer
Preface. FSDM (2008)
Rubén Armañanzas, Iñaki Inza, Roberto Santana, Yvan Saeys, Jose Luis Flores, José Antonio Lozano, Yves Van de Peer, Rosa Blanco, Víctor Robles, Concha Bielza, Pedro Larrañaga
A review of estimation of distribution algorithms in bioinformatics. BioData Min. 1 (2008)
Yvan Saeys, Thomas Abeel, Yves Van de Peer
Robust Feature Selection Using Ensemble Feature Selection Techniques. ECML/PKDD (2) (2008)
Michiel Van Bel, Yvan Saeys, Yves Van de Peer
FunSiP: a modular and extensible classifier for the prediction of functional sites in DNA. Bioinform. 24 (13) (2008)
Thomas Abeel, Yvan Saeys, Pierre Rouzé, Yves Van de Peer
ProSOM: core promoter prediction based on unsupervised clustering of DNA physical profiles. ISMB (2008)
Yvan Saeys, Thomas Abeel, Sven Degroeve, Yves Van de Peer
Translation initiation site prediction on a genomic scale: beauty in simplicity. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Yvan Saeys, Iñaki Inza, Pedro Larrañaga
A review of feature selection techniques in bioinformatics. Bioinform. 23 (19) (2007)
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
Validating module network learning algorithms using simulated data. BMC Bioinform. 8 (S-2) (2007)
Yvan Saeys, Pierre Rouzé, Yves Van de Peer
In search of the small ones: improved prediction of short exons in vertebrates, plants, fungi and protists. Bioinform. 23 (4) (2007)
Isis Bonet, María M. García, Yvan Saeys, Yves Van de Peer, Ricardo Grau Ábalo
Predicting Human Immunodeficiency Virus (HIV) Drug Resistance Using Recurrent Neural Networks. IWINAC (1) (2007)
Yvan Saeys, Yves Van de Peer
Enhancing Coding Potential Prediction for Short Sequences Using Complementary Sequence Features and Feature Selection. KDECB (2006)
Isis Bonet, Yvan Saeys, Ricardo Grau Ábalo, María M. García, Robersy Sanchez, Yves Van de Peer
Feature Extraction Using Clustering of Protein. CIARP (2006)
Philippe Faes, Bram Minnaert, Mark Christiaens, Eric Bonnet, Yvan Saeys, Dirk Stroobandt, Yves Van de Peer
Scalable hardware accelerator for comparing DNA and protein sequences. Infoscale (2006)
Ronald L. Westra, Karl Tuyls, Yvan Saeys, Ann Nowé
Knowledge Discovery and Emergent Complexity in Bioinformatics. KDECB (2006)
Sven Degroeve, Yvan Saeys, Bernard De Baets, Pierre Rouzé, Yves Van de Peer
SpliceMachine: predicting splice sites from high-dimensional local context representations. Bioinform. 21 (8) (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yvan Saeys