Learning Structure with Many-Take-All Networks. - David M. J. Tax; Hilbert J. Kappen (ICANN, 1996)

Experiments with a featureless approach to pattern recognition. - Robert P. W. Duin; Dick de Ridder; David M. J. Tax (Pattern Recognit. Lett., 1997)

Classifier Conditional Posterior Probabilities. - Robert P. W. Duin; David M. J. Tax (SSPR/SPR, 1998)

Outlier Detection Using Classifier Instability. - David M. J. Tax; Robert P. W. Duin (SSPR/SPR, 1998)

Handwritten digit recognition by combined classifiers. - Martijn van Breukelen; Robert P. W. Duin; David M. J. Tax; J. E. den Hartog (Kybernetika, 1998)

Featureless pattern classification. - Robert P. W. Duin; Dick de Ridder; David M. J. Tax (Kybernetika, 1998)

Data domain description using support vectors. - David M. J. Tax; Robert P. W. Duin (ESANN, 1999)

Pump Failure Detection Using Support Vector Data Descriptions. - David M. J. Tax; Alexander Ypma; Robert P. W. Duin (IDA, 1999)

Support vector domain description. - David M. J. Tax; Robert P. W. Duin (Pattern Recognit. Lett., 1999)

Data Description in Subspaces. - David M. J. Tax; Robert P. W. Duin (ICPR, 2000)

Experiments with Classifier Combining Rules. - Robert P. W. Duin; David M. J. Tax (Multiple Classifier Systems, 2000)

Combining multiple classifiers by averaging or by multiplying? - David M. J. Tax; Martijn van Breukelen; Robert P. W. Duin; Josef Kittler (Pattern Recognit., 2000)

Combining One-Class Classifiers. - David M. J. Tax; Robert P. W. Duin (Multiple Classifier Systems, 2001)

Uniform Object Generation for Optimizing One-class Classifiers. - David M. J. Tax; Robert P. W. Duin (J. Mach. Learn. Res., 2001)

Using Two-Class Classifiers for Multiclass Classification. - David M. J. Tax; Robert P. W. Duin (ICPR (2), 2002)

On Combining One-Class Classifiers for Image Database Retrieval. - Carmen Lai; David M. J. Tax; Robert P. W. Duin; Elzbieta Pekalska; Pavel Paclík (Multiple Classifier Systems, 2002)

One-Class LP Classifiers for Dissimilarity Representations. - Elzbieta Pekalska; David M. J. Tax; Robert P. W. Duin (NIPS, 2002)

Feature Extraction for One-Class Classification. - David M. J. Tax; Klaus-Robert Müller (ICANN, 2003)

Online SVM learning: from classification to data description and back. - David M. J. Tax; Pavel Laskov (NNSP, 2003)

Kernel Whitening for One-Class Classification. - David M. J. Tax; Piotr Juszczak (Int. J. Pattern Recognit. Artif. Intell., 2003)

Visual Object Recognition Through One-Class Learning. - QingHua Wang; Luís Seabra Lopes; David M. J. Tax (ICIAR (1), 2004)

The Characterization of Classification Problems by Classifier Disagreements. - Robert P. W. Duin; Elzbieta Pekalska; David M. J. Tax (ICPR (1), 2004)

A Consistency-Based Model Selection for One-Class Classification. - David M. J. Tax; Klaus-Robert Müller (ICPR (3), 2004)

Cost-Based Classifier Evaluation for Imbalanced Problems. - Thomas C. W. Landgrebe; Pavel Paclík; David M. J. Tax; Serguei Verzakov; Robert P. W. Duin (SSPR/SPR, 2004)

A Study On Combining Image Representations For Image Classification And Retrieval. - Carmen Lai; David M. J. Tax; Robert P. W. Duin; Elzbieta Pekalska; Pavel Paclík (Int. J. Pattern Recognit. Artif. Intell., 2004)

Support Vector Data Description. - David M. J. Tax; Robert P. W. Duin (Mach. Learn., 2004)

Turning the hyperparameter of an AUC-optimized classifier. - David M. J. Tax; Cor J. Veenman (BNAIC, 2005)

A Weighted Nearest Mean Classifier for Sparse Subspaces. - Cor J. Veenman; David M. J. Tax (CVPR (2), 2005)

Optimising Two-Stage Recognition Systems. - Thomas C. W. Landgrebe; Pavel Paclík; David M. J. Tax; Robert P. W. Duin (Multiple Classifier Systems, 2005)

On Deriving the Second-Stage Training Set for Trainable Combiners. - Pavel Paclík; Thomas C. W. Landgrebe; David M. J. Tax; Robert P. W. Duin (Multiple Classifier Systems, 2005)

LESS: A Model-Based Classifier for Sparse Subspaces. - Cor J. Veenman; David M. J. Tax (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs. - Yulia Arzhaeva; Bram van Ginneken; David M. J. Tax (ICPR (1), 2006)

Domain Based LDA and QDA. - Piotr Juszczak; David M. J. Tax; Serguei Verzakov; Robert P. W. Duin (ICPR (2), 2006)

Linear model combining by optimizing the Area under the ROC curve. - David M. J. Tax; Robert P. W. Duin (ICPR (4), 2006)

Improving computer-aided diagnosis of interstitial disease in chest radiographs by combining one-class and two-class classifiers. - Yulia Arzhaeva; David M. J. Tax; Bram van Ginneken (Image Processing, 2006)

Outlier Detection Using Ball Descriptions with Adjustable Metric. - David M. J. Tax; Piotr Juszczak; Elzbieta Pekalska; Robert P. W. Duin (SSPR/SPR, 2006)

From outliers to prototypes: Ordering data. - Stefan Harmeling; Guido Dornhege; David M. J. Tax; Frank C. Meinecke; Klaus-Robert Müller (Neurocomputing, 2006)

The interaction between classification and reject performance for distance-based reject-option classifiers. - Thomas C. W. Landgrebe; David M. J. Tax; Pavel Paclík; Robert P. W. Duin (Pattern Recognit. Lett., 2006)

A Fast Approach to Improve Classification Performance of ECOC Classification Systems. - Paolo Simeone; David M. J. Tax; Robert P. W. Duin; Francesco Tortorella (SSPR/SPR, 2008)

Learning Curves for the Analysis of Multiple Instance Classifiers. - David M. J. Tax; Robert P. W. Duin (SSPR/SPR, 2008)

Subclass Problem-Dependent Design for Error-Correcting Output Codes. - Sergio Escalera; David M. J. Tax; Oriol Pujol; Petia Radeva; Robert P. W. Duin (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Growing a multi-class classifier with a reject option. - David M. J. Tax; Robert P. W. Duin (Pattern Recognit. Lett., 2008)

Maximum Membership Scale Selection. - Marco Loog; Yan Li 009; David M. J. Tax (MCS, 2009)

Optimal Mean-Precision Classifier. - David M. J. Tax; Marco Loog; Robert P. W. Duin (MCS, 2009)

Minimum spanning tree based one-class classifier. - Piotr Juszczak; David M. J. Tax; Elzbieta Pekalska; Robert P. W. Duin (Neurocomputing, 2009)

Dissimilarity-based classification in the absence of local ground truth: Application to the diagnostic interpretation of chest radiographs. - Yulia Arzhaeva; David M. J. Tax; Bram van Ginneken (Pattern Recognit., 2009)

Component-based discriminative classification for hidden Markov models. - Manuele Bicego; Elzbieta Pekalska; David M. J. Tax; Robert P. W. Duin (Pattern Recognit., 2009)

Feature-Based Dissimilarity Space Classification. - Robert P. W. Duin; Marco Loog; Elzbieta Pekalska; David M. J. Tax (ICPR Contests, 2010)

The Detection of Concept Frames Using Clustering Multi-instance Learning. - David M. J. Tax; E. Hendriks; Michel François Valstar; Maja Pantic (ICPR, 2010)

Dissimilarity-Based Multiple Instance Learning. - Lauge Sørensen; Marco Loog; David M. J. Tax; Wan-Jui Lee; Marleen de Bruijne; Robert P. W. Duin (SSPR/SPR, 2010)

Pruned Random Subspace Method for One-Class Classifiers. - Veronika Cheplygina; David M. J. Tax (MCS, 2011)

TUD-MM at MediaEval 2011 Genre Tagging Task: Video search reranking for genre tagging. - Peng Xu; David M. J. Tax; Alan Hanjalic (MediaEval, 2011)

Supervised Scale-Invariant Segmentation (and Detection). - Yan Li 009; David M. J. Tax; Marco Loog (SSVM, 2011)

Bag Dissimilarities for Multiple Instance Learning. - David M. J. Tax; Marco Loog; Robert P. W. Duin; Veronika Cheplygina; Wan-Jui Lee (SIMBAD, 2011)

Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features. - Babak Loni; Gijs van Tulder; Pascal Wiggers; David M. J. Tax; Marco Loog (TSD, 2011)

Qualitative Evaluation of Detection and Tracking Performance. - Swaminathan Sankaranarayanan; François Brémond; David M. J. Tax (AVSS, 2012)

Does one rotten apple spoil the whole barrel? - Veronika Cheplygina; David M. J. Tax; Marco Loog (ICPR, 2012)

A structure-based video representation for web video categorization. - Peng Xu; David M. J. Tax; Alan Hanjalic (ICPR, 2012)

Class-Dependent Dissimilarity Measures for Multiple Instance Learning. - Veronika Cheplygina; David M. J. Tax; Marco Loog (SSPR/SPR, 2012)

Bridging Structure and Feature Representations in Graph Matching. - Wan-Jui Lee; Veronika Cheplygina; David M. J. Tax; Marco Loog; Robert P. W. Duin (Int. J. Pattern Recognit. Artif. Intell., 2012)

Scale selection for supervised image segmentation. - Yan Li 009; David M. J. Tax; Marco Loog (Image Vis. Comput., 2012)

Online face recognition and learning for cognitive robots. - Floris Gaisser; Maja Rudinac; Pieter P. Jonker; David M. J. Tax (ICAR, 2013)

Combining Instance Information to Classify Bags. - Veronika Cheplygina; David M. J. Tax; Marco Loog (MCS, 2013)

The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples. - Yan Li 009; David M. J. Tax; Robert P. W. Duin; Marco Loog (MCS, 2013)

On the Informativeness of Asymmetric Dissimilarities. - Yenisel Plasencia Calana; Veronika Cheplygina; Robert P. W. Duin; Edel B. García Reyes; Mauricio Orozco-Alzate; David M. J. Tax; Marco Loog (SIMBAD, 2013)

Multiple-instance learning as a classifier combining problem. - Yan Li 009; David M. J. Tax; Robert P. W. Duin; Marco Loog (Pattern Recognit., 2013)

Classification of COPD with Multiple Instance Learning. - Veronika Cheplygina; Lauge Sørensen; David M. J. Tax; Jesper Johannes Holst Pedersen; Marco Loog; Marleen de Bruijne (ICPR, 2014)

The Effect of Aggregating Subtype Performances Depends Strongly on the Performance Measure Used. - David M. J. Tax; Herman M. J. Sontrop; Marcel J. T. Reinders; Perry D. Moerland (ICPR, 2014)

Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder. - Veronika Cheplygina; David M. J. Tax; Marco Loog; Aasa Feragen (MLMI, 2014)

Evaluating Classification Performance with only Positive and Unlabeled Samples. - Siamak Hajizadeh; Zili Li 003; Rolf P. B. J. Dollevoet; David M. J. Tax (S+SSPR, 2014)

Quantile Representation for Indirect Immunofluorescence Image Classification. - David M. J. Tax; Veronika Cheplygina; Marco Loog (CoRR, 2014)

Real-time estimation of surgical procedure duration. - A. C. P. Guédon; M. Paalvast; Frédérique C. Meeuwsen; David M. J. Tax; A. P. van Dijke; L. S. G. L. Wauben; M. van der Elst; Jenny Dankelman; John van den Dobbelsteen (HealthCom, 2015)

Label Stability in Multiple Instance Learning. - Veronika Cheplygina; Lauge Sørensen; David M. J. Tax; Marleen de Bruijne; Marco Loog (MICCAI (1), 2015)

Characterizing Multiple Instance Datasets. - Veronika Cheplygina; David M. J. Tax (SIMBAD, 2015)

An Adaptive Radial Basis Function Kernel for Support Vector Data Description. - André Eugênio Lazzaretti; David M. J. Tax (SIMBAD, 2015)

Time Series Classification using the Hidden-Unit Logistic Model. - Wenjie Pei; Hamdi Dibeklioglu; David M. J. Tax; Laurens van der Maaten (CoRR, 2015)

Single- vs. multiple-instance classification. - Ethem Alpaydin; Veronika Cheplygina; Marco Loog; David M. J. Tax (Pattern Recognit., 2015)

Multiple instance learning with bag dissimilarities. - Veronika Cheplygina; David M. J. Tax; Marco Loog (Pattern Recognit., 2015)

On classification with bags, groups and sets. - Veronika Cheplygina; David M. J. Tax; Marco Loog (Pattern Recognit. Lett., 2015)

Robust Gram Embeddings. - Taygun Kekeç; David M. J. Tax (EMNLP, 2016)

Regularizing AdaBoost with validation sets of increasing size. - Dirk W. J. Meijer; David M. J. Tax (ICPR, 2016)

Class-dependent, non-convex losses to optimize precision. - David M. J. Tax; Feng Wang (ICPR, 2016)

The Similarity Between Dissimilarities. - David M. J. Tax; Veronika Cheplygina; Robert P. W. Duin; Jan van de Poll (S+SSPR, 2016)

Modeling Time Series Similarity with Siamese Recurrent Networks. - Wenjie Pei; David M. J. Tax; Laurens van der Maaten (CoRR, 2016)

Survey on the attention based RNN model and its applications in computer vision. - Feng Wang; David M. J. Tax (CoRR, 2016)

Novelty detection and multi-class classification in power distribution voltage waveforms. - André Eugênio Lazzaretti; David Martinus Johannes Tax; Hugo Vieira Neto; Vitor Hugo Ferreira (Expert Syst. Appl., 2016)

'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies. - Annetje C. P. Guédon; M. Paalvast; Frédérique C. Meeuwsen; David M. J. Tax; A. P. van Dijke; L. S. G. L. Wauben; M. van der Elst; Jenny Dankelman; John van den Dobbelsteen (J. Medical Syst., 2016)

Dissimilarity-Based Ensembles for Multiple Instance Learning. - Veronika Cheplygina; David M. J. Tax; Marco Loog (IEEE Trans. Neural Networks Learn. Syst., 2016)

Interacting Attention-gated Recurrent Networks for Recommendation. - Wenjie Pei; Jie Yang 028; Zhu Sun 001; Jie Zhang 002; Alessandro Bozzon; David M. J. Tax (CIKM, 2017)

Temporal Attention-Gated Model for Robust Sequence Classification. - Wenjie Pei; Tadas Baltrusaitis; David M. J. Tax; Louis-Philippe Morency (CVPR, 2017)

PAWE: Polysemy Aware Word Embeddings. - Taygun Kekeç; Laurens van der Maaten; David M. J. Tax (ICISDM, 2018)

Improving Temporal Interpolation of Head and Body Pose using Gaussian Process Regression in a Matrix Completion Setting. - Stephanie Tan; David M. J. Tax; Hayley Hung (GIFT@ICMI, 2018)

Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning. - Antonella Mensi; Manuele Bicego; Pietro Lovato; Marco Loog; David M. J. Tax (S+SSPR, 2018)

Unsupervised Learning of Sequence Representations by Autoencoders. - Wenjie Pei; David M. J. Tax (CoRR, 2018)

Example and Feature importance-based Explanations for Black-box Machine Learning Models. - Ajaya Adhikari; David M. J. Tax; Riccardo Satta; Matthias Faeth (CoRR, 2018)

Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model. - Wenjie Pei; Hamdi Dibeklioglu; David M. J. Tax; Laurens van der Maaten (IEEE Trans. Neural Networks Learn. Syst., 2018)

LEAFAGE: Example-based and Feature importance-based Explanations for Black-box ML models. - Ajaya Adhikari; David M. J. Tax; Riccardo Satta; Matthias Faeth (FUZZ-IEEE, 2019)

Boosted negative sampling by quadratically constrained entropy maximization. - Taygun Kekeç; David Mimno; David M. J. Tax (Pattern Recognit. Lett., 2019)

A dissimilarity-based multiple instance learning approach for protein remote homology detection. - Antonella Mensi; Manuele Bicego; Pietro Lovato; Marco Loog; David M. J. Tax (Pattern Recognit. Lett., 2019)

Proximity Isolation Forests. - Antonella Mensi; Manuele Bicego; David M. J. Tax (ICPR, 2020)

An Alternative Exploitation of Isolation Forests for Outlier Detection. - Antonella Mensi; Alessio Franzoni; David M. J. Tax; Manuele Bicego (S+SSPR, 2020)

A Brief Prehistory of Double Descent. - Marco Loog; Tom J. Viering; Alexander Mey; Jesse H. Krijthe; David M. J. Tax (CoRR, 2020)

Attended End-to-End Architecture for Age Estimation From Facial Expression Videos. - Wenjie Pei; Hamdi Dibeklioglu; Tadas Baltrusaitis; David M. J. Tax (IEEE Trans. Image Process., 2020)

Gestures In-The-Wild: Detecting Conversational Hand Gestures in Crowded Scenes Using a Multimodal Fusion of Bags of Video Trajectories and Body Worn Acceleration. - Laura Cabrera Quiros; David M. J. Tax; Hayley Hung (IEEE Trans. Multim., 2020)

Head and Body Orientation Estimation with Sparse Weak Labels in Free Standing Conversational Settings. - Stephanie Tan; David M. J. Tax; Hayley Hung (DYAD@ICCV, 2021)

Multimodal Joint Head Orientation Estimation in Interacting Groups via Proxemics and Interaction Dynamics. - Stephanie Tan; David M. J. Tax; Hayley Hung (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

Sem2Vec: Semantic Word Vectors with Bidirectional Constraint Propagations. - Taygun Kekeç; David M. J. Tax (IEEE Trans. Knowl. Data Eng., 2021)

A View on Model Misspecification in Uncertainty Quantification. - Yuko Kato; David M. J. Tax; Marco Loog (BNAIC/BENELEARN, 2022)

Conversation Group Detection With Spatio-Temporal Context. - Stephanie Tan; David M. J. Tax; Hayley Hung (ICMI, 2022)

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography. - Morteza Moradi 002; Ramin Ghorbani; Stefano Sfarra; David M. J. Tax; Dimitrios Zarouchas (Sensors, 2022)

A Review of Nonconformity Measures for Conformal Prediction in Regression. - Yuko Kato; David M. J. Tax; Marco Loog (COPA, 2023)

Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability. - Ramin Ghorbani; Marcel J. T. Reinders; David M. J. Tax (ICMLT, 2023)

Rolling-Horizon Simulation Optimization For A Multi-Objective Biomanufacturing Scheduling Problem. - Kim van den Houten; Mathijs de Weerdt; David M. J. Tax; Esteban Freydell; Eva Christoupoulou; Alessandro Nati (WSC, 2023)

Improving performance of heart rate time series classification by grouping subjects. - Michael Beekhuizen; Arman Naseri; David M. J. Tax; Ivo van der Bilt; Marcel J. T. Reinders (CoRR, 2023)

Learning From Scenarios for Stochastic Repairable Scheduling. - Kim van den Houten; David M. J. Tax; Esteban Freydell; Mathijs de Weerdt (CoRR, 2023)

Detecting outliers from pairwise proximities: Proximity isolation forests. - Antonella Mensi; David M. J. Tax; Manuele Bicego (Pattern Recognit., 2023)

Continual prune-and-select: class-incremental learning with specialized subnetworks. - Aleksandr Dekhovich; David M. J. Tax; Marcel H. F. Sluiter; Miguel A. Bessa (Appl. Intell., 2023)

Learning from Scenarios for Repairable Stochastic Scheduling. - Kim van den Houten; David M. J. Tax; Esteban Freydell; Mathijs de Weerdt (CPAIOR (2), 2024)

PATE: Proximity-Aware Time Series Anomaly Evaluation. - Ramin Ghorbani; Marcel J. T. Reinders; David M. J. Tax (KDD, 2024)

RESTAD: Reconstruction and Similarity Based Transformer for Time Series Anomaly Detection. - Ramin Ghorbani; Marcel J. T. Reinders; David M. J. Tax (MLSP, 2024)

Personalized anomaly detection in PPG data using representation learning and biometric identification. - Ramin Ghorbani; Marcel J. T. Reinders; David M. J. Tax (Biomed. Signal Process. Control., 2024)

Learning solutions of parametric Navier-Stokes with physics-informed neural networks. - Mahdi Naderibeni; Marcel J. T. Reinders; Liang Wu; David M. J. Tax (CoRR, 2024)

Inductive Conformal Prediction under Data Scarcity: Exploring the Impacts of Nonconformity Measures. - Yuko Kato; David M. J. Tax; Marco Loog (CoRR, 2024)

Neural network relief: a pruning algorithm based on neural activity. - Aleksandr Dekhovich; David M. J. Tax; Marcel H. F. Sluiter; Miguel A. Bessa (Mach. Learn., 2024)

Proactive and Reactive Constraint Programming for Stochastic Project Scheduling with Maximal Time-Lags. - Kim van den Houten; Léon Planken; Esteban Freydell; David M. J. Tax; Mathijs de Weerdt (AAAI, 2025)

iPINNs: incremental learning for Physics-informed neural networks. - Aleksandr Dekhovich; Marcel H. F. Sluiter; David M. J. Tax; Miguel A. Bessa (Eng. Comput., 2025)

Learning Learning Curves. - O. Taylan Turan; David M. J. Tax; Tom J. Viering; Marco Loog (Pattern Anal. Appl., 2025)