A robust non-linear projection method. - John Aldo Lee; Amaury Lendasse; Nicolas Donckers; Michel Verleysen (ESANN, 2000)

Time series forecasting using CCA and Kohonen maps - application to electricity consumption. - Amaury Lendasse; John Aldo Lee; Vincent Wertz; Michel Verleysen (ESANN, 2000)

Input data reduction for the prediction of financial time series. - Amaury Lendasse; John Aldo Lee; Eric de Bodt; Vincent Wertz; Michel Verleysen (ESANN, 2001)

Recursive learning rules for SOMs. - John A. Lee 001; Nicolas Donckers; Michel Verleysen (WSOM, 2001)

Width optimization of the Gaussian kernels in Radial Basis Function Networks. - Nabil Benoudjit; Cédric Archambeau; Amaury Lendasse; John Aldo Lee; Michel Verleysen (ESANN, 2002)

Curvilinear Distance Analysis versus Isomap. - John Aldo Lee; Amaury Lendasse; Michel Verleysen (ESANN, 2002)

Nonlinear Projection with the Isotop Method. - John Aldo Lee; Michel Verleysen (ICANN, 2002)

Forecasting electricity consumption using nonlinear projection and self-organizing maps. - Amaury Lendasse; John Aldo Lee; Vincent Wertz; Michel Verleysen (Neurocomputing, 2002)

Self-organizing maps with recursive neighborhood adaptation. - John Aldo Lee; Michel Verleysen (Neural Networks, 2002)

On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures. - Cédric Archambeau; John Aldo Lee; Michel Verleysen (ESANN, 2003)

Locally Linear Embedding versus Isotop. - John Aldo Lee; Cédric Archambeau; Michel Verleysen (ESANN, 2003)

Improving independent component analysis performances by variable selection. - Frédéric Vrins; John Aldo Lee; Michel Verleysen; Vincent Vigneron; Christian Jutten (NNSP, 2003)

Analysis of high-dimensional numerical data: from principal component analysis to non-linear dimensionality reduction and blind source separation. - John Aldo Lee (2003)

How to project 'circular' manifolds using geodesic distances? - John Aldo Lee; Michel Verleysen (ESANN, 2004)

Non-linear ICA by Using Isometric Dimensionality Reduction. - John Aldo Lee; Christian Jutten; Michel Verleysen (ICA, 2004)

Double quantization forecasting method for filling missing data in the CATS time series. - Geoffroy Simon; John Aldo Lee; Michel Verleysen; Marie Cottrell (IJCNN, 2004)

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis. - John Aldo Lee; Amaury Lendasse; Michel Verleysen (Neurocomputing, 2004)

A simple ICA algorithm for non-differentiable contrasts. - John Aldo Lee; Frédéric Vrins; Michel Verleysen (EUSIPCO, 2005)

Can we always trust entropy minima in the ICA context? - Frédéric Vrins; John Aldo Lee; Michel Verleysen (EUSIPCO, 2005)

Filtering-Free Blind Separation of Correlated Images. - Frédéric Vrins; John Aldo Lee; Michel Verleysen (IWANN, 2005)

Nonlinear dimensionality reduction of data manifolds with essential loops. - John Aldo Lee; Michel Verleysen (Neurocomputing, 2005)

Non-orthogonal Support Width ICA. - John Aldo Lee; Frédéric Vrins; Michel Verleysen (ESANN, 2006)

Unfolding preprocessing for meaningful time series clustering. - Geoffroy Simon; John Aldo Lee; Michel Verleysen (Neural Networks, 2006)

Forecasting the CATS benchmark with the Double Vector Quantization method. - Geoffroy Simon; John Aldo Lee; Marie Cottrell; Michel Verleysen (Neurocomputing, 2007)

A Minimum-Range Approach to Blind Extraction of Bounded Sources. - Frédéric Vrins; John Aldo Lee; Michel Verleysen (IEEE Trans. Neural Networks, 2007)

Rank-based quality assessment of nonlinear dimensionality reduction. - John Aldo Lee; Michel Verleysen (ESANN, 2008)

Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition. - John Aldo Lee; Frédéric Vrins; Michel Verleysen (Neurocomputing, 2008)

Quality assessment of nonlinear dimensionality reduction based on K-ary neighborhoods. - John Aldo Lee; Michel Verleysen (FSDM, 2008)

Edge-Preserving Filtering of Images with Low Photon Counts. - John Aldo Lee; Xavier Geets; Vincent Grégoire; Anne Bol (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Patch-based bilateral filter and local m-smoother for image denoising. - Arnaud de Decker; John Aldo Lee; Michel Verleysen (ESANN, 2009)

Adaptive anisotropic denoising: a bootstrapped procedure. - John Aldo Lee; Arnaud de Decker; Michel Verleysen (ESANN, 2009)

Simbed: Similarity-Based Embedding. - John Aldo Lee; Michel Verleysen (ICANN (2), 2009)

Quality assessment of dimensionality reduction: Rank-based criteria. - John Aldo Lee; Michel Verleysen (Neurocomputing, 2009)

On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding. - John A. Lee 001; Michel Verleysen (COMPSTAT, 2010)

Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning. - Axel Wismüller; Michel Verleysen; Michaël Aupetit 001; John Aldo Lee (ESANN, 2010)

Unsupervised dimensionality reduction: Overview and recent advances. - John Aldo Lee; Michel Verleysen (IJCNN, 2010)

Dimensionality reduction by rank preservation. - Victor Onclinx; John Aldo Lee; Vincent Wertz; Michel Verleysen (IJCNN, 2010)

Advances in computational intelligence and learning (ESANN 2009). - Cecilio Angulo; John Aldo Lee; Frank-Michael Schleif (Neurocomputing, 2010)

A principled approach to image denoising with similarity kernels involving patches. - Arnaud de Decker; John Aldo Lee; Michel Verleysen (Neurocomputing, 2010)

Scale-independent quality criteria for dimensionality reduction. - John Aldo Lee; Michel Verleysen (Pattern Recognit. Lett., 2010)

Mode estimation in high-dimensional spaces with flat-top kernels: Application to image denoising. - Arnaud de Decker; Damien François; Michel Verleysen; John Aldo Lee (Neurocomputing, 2011)

Advances in artificial neural networks, machine learning, and computational intelligence. - John Aldo Lee; Frank-Michael Schleif; Thomas Martinetz (Neurocomputing, 2011)

Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants. - John Aldo Lee; Michel Verleysen (ICCS, 2011)

Incremental feature building and classification for image segmentation. - Guillaume Bernard 001; Michel Verleysen; John Aldo Lee (ESANN, 2012)

Type 1 and 2 symmetric divergences for stochastic neighbor embedding. - John Aldo Lee (ESANN, 2012)

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011). - John Aldo Lee; Petra Schneider; John A. Quinn (Neurocomputing, 2012)

Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy. - Tony Shepherd; Mika Teräs; Reinhard Beichel; Ronald Boellaard; Michel Bruynooghe; Volker Dicken; Mark J. Gooding; Peter J. Julyan; John Aldo Lee; Sébastien Lefèvre; Michael Mix; Valery Naranjo; et al. (IEEE Trans. Medical Imaging, 2012)

Sensitivity to parameter and data variations in dimensionality reduction techniques. - Francisco J. García-Fernández; Michel Verleysen; John Aldo Lee; Ignacio Díaz Blanco (ESANN, 2013)

Segmentation with Incremental Classifiers. - Guillaume Bernard 001; Michel Verleysen; John Aldo Lee (ICIAP (2), 2013)

Nonlinear Dimensionality Reduction for Visualization. - Michel Verleysen; John Aldo Lee (ICONIP (1), 2013)

Improving projection-based data analysis by feature space transformations. - Matthias Schäfer 001; Leishi Zhang; Tobias Schreck; Andrada Tatu; John Aldo Lee; Michel Verleysen; Daniel A. Keim (Visualization and Data Analysis, 2013)

Stability Comparison of Dimensionality Reduction Techniques Attending to Data and Parameter Variations. - Francisco J. García-Fernández; Michel Verleysen; John A. Lee 001; Ignacio Díaz Blanco (VAMP@EuroVis, 2013)

Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. - John Aldo Lee; Emilie Renard; Guillaume Bernard 001; Pierre Dupont; Michel Verleysen (Neurocomputing, 2013)

Two key properties of dimensionality reduction methods. - John Aldo Lee; Michel Verleysen (CIDM, 2014)

Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. - Diego Hernán Peluffo-Ordóñez; John Aldo Lee; Michel Verleysen (CIDM, 2014)

Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction. - John Aldo Lee; Diego Hernán Peluffo-Ordóñez; Michel Verleysen (ESANN, 2014)

Recent methods for dimensionality reduction: A brief comparative analysis. - Diego Hernán Peluffo-Ordóñez; John Aldo Lee; Michel Verleysen (ESANN, 2014)

Unsupervised Relevance Analysis for Feature Extraction and Selection - A Distance-based Approach for Feature Relevance. - Diego Hernán Peluffo-Ordóñez; John Aldo Lee; Michel Verleysen; José L. Rodríguez; Germán Castellanos-Domínguez (ICPRAM, 2014)

Short Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding. - Diego Hernán Peluffo-Ordóñez; John Aldo Lee; Michel Verleysen (WSOM, 2014)

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013). - Mark J. Embrechts; Fabrice Rossi; Frank-Michael Schleif; John Aldo Lee (Neurocomputing, 2014)

Unsupervised dimensionality reduction: the challenge of big data visualization. - Kerstin Bunte; John Aldo Lee (ESANN, 2015)

Geometrical homotopy for data visualization. - Diego Hernán Peluffo-Ordóñez; Juan Carlos Alvarado-Pérez; John Aldo Lee; Michel Verleysen (ESANN, 2015)

Post-reconstruction deconvolution of PET images by total generalized variation regularization. - Stéphanie Guérit; Laurent Jacques; Benoît Macq; John A. Lee 001 (EUSIPCO, 2015)

Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding. - Romain Hérault; Jérémie Boulanger; Ludovic Seifert; John Aldo Lee (MLSA@PKDD/ECML, 2015)

Incremental classification of objects in scenes: Application to the delineation of images. - Guillaume Bernard 001; Michel Verleysen; John Aldo Lee (Neurocomputing, 2015)

Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure. - John Aldo Lee; Diego Hernán Peluffo-Ordóñez; Michel Verleysen (Neurocomputing, 2015)

Human-centered machine learning through interactive visualization: review and open challenges. - Dominik Sacha; Michael Sedlmair; Leishi Zhang; John Aldo Lee; Daniel Weiskopf; Stephen C. North; Daniel A. Keim (ESANN, 2016)

Image deconvolution by local order preservation of pixels values. - Stéphanie Guérit; Laurent Jacques; John A. Lee 001 (EUSIPCO, 2016)

Multi-step-ahead forecasting using kernel adaptive filtering. - Sergio García-Vega; Germán Castellanos-Domínguez; Michel Verleysen; John Aldo Lee (IJCNN, 2016)

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). - Vinayak Abrol; Olivier Absil; Pierre-Antoine Absil; Sandrine Anthoine; Philippe Antoine; Thomas Arildsen; Nancy Bertin; Folkert Bleichrodt; Jérôme Bobin; Anne Bol; Antoine Bonnefoy; Francesco Caltagirone; et al. (CoRR, 2016)

Blind Deconvolution of PET Images using Anatomical Priors. - Stéphanie Guérit; Adriana Gonzalez; Anne Bol; John A. Lee 001; Laurent Jacques (CoRR, 2016)

Large-scale nonlinear dimensionality reduction for network intrusion detection. - Yasir Hamid; Ludovic Journaux; John Aldo Lee; Lucile Sautot; Nabi Bushra; M. Sugumaran (ESANN, 2017)

Comparing dynamics of fluency and inter-limb coordination in climbing activities using multi-scale Jensen-Shannon embedding and clustering. - Romain Hérault; Dominic Orth; Ludovic Seifert; Jérémie Boulanger; John Aldo Lee (Data Min. Knowl. Discov., 2017)

Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity. - Andrés Marino Álvarez-Meza; John Aldo Lee; Michel Verleysen; Germán Castellanos-Domínguez (Neurocomputing, 2017)

What you see is what you can change: Human-centered machine learning by interactive visualization. - Dominik Sacha; Michael Sedlmair; Leishi Zhang; John Aldo Lee; Jaakko Peltonen; Daniel Weiskopf; Stephen C. North; Daniel A. Keim (Neurocomputing, 2017)

Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis. - Dominik Sacha; Leishi Zhang; Michael Sedlmair; John Aldo Lee; Jaakko Peltonen; Daniel Weiskopf; Stephen C. North; Daniel A. Keim (IEEE Trans. Vis. Comput. Graph., 2017)

Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet. - Umair Javaid; Damien Dasnoy; John A. Lee 001 (ACIVS, 2018)

Contour Propagation in CT Scans with Convolutional Neural Networks. - Jean Léger; Eliott Brion; Umair Javaid; John A. Lee 001; Christophe De Vleeschouwer; Benoît Macq (ACIVS, 2018)

Perplexity-free t-SNE and twice Student tt-SNE. - Cyril de Bodt; Dounia Mulders; Michel Verleysen; John A. Lee 001 (ESANN, 2018)

Extensive assessment of Barnes-Hut t-SNE. - Cyril de Bodt; Dounia Mulders; Michel Verleysen; John A. Lee 001 (ESANN, 2018)

Information visualisation and machine learning: latest trends towards convergence. - Benoît Frénay; Bruno Dumas; John A. Lee 001 (ESANN, 2018)

Capturing variabilities from Computed Tomography images with Generative Adversarial Networks (GANs). - Umair Javaid; John A. Lee 001 (ESANN, 2018)

Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks. - Umair Javaid; John A. Lee 001 (CoRR, 2018)

Compressive Sampling Approach for Image Acquisition with Lensless Endoscope. - Stéphanie Guérit; Siddharth Sivankutty; Camille Scotté; John Aldo Lee; Hervé Rigneault; Laurent Jacques (CoRR, 2018)

A novel method for network intrusion detection based on nonlinear SNE and SVM. - Yasir Hamid; Ludovic Journaux; John A. Lee 001; M. Sugumaran (Int. J. Artif. Intell. Soft Comput., 2018)

Class-aware t-SNE: cat-SNE. - Cyril de Bodt; Dounia Mulders; Daniel López Sánchez; Michel Verleysen; John A. Lee 001 (ESANN, 2019)

Tensor factorization to extract patterns in multimodal EEG data. - Dounia Mulders; Cyril de Bodt; Nicolas Lejeune; John A. Lee 001; André Mouraux; Michel Verleysen (ESANN, 2019)

Using planning CTs to enhance CNN-based bladder segmentation on cone beam CT. - Eliott Brion; Jean Léger; Umair Javaid; John A. Lee 001; Christophe De Vleeschouwer; Benoît Macq (Image-Guided Procedures, 2019)

Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation. - Umair Javaid; Damien Dasnoy; John A. Lee 001 (Image Processing, 2019)

Nonlinear Dimensionality Reduction With Missing Data Using Parametric Multiple Imputations. - Cyril de Bodt; Dounia Mulders; Michel Verleysen; John Aldo Lee (IEEE Trans. Neural Networks Learn. Syst., 2019)

Perplexity-free Parametric t-SNE. - Francesco Crecchi; Cyril de Bodt; Michel Verleysen; John A. Lee 001; Davide Bacciu (ESANN, 2020)

Stochastic quartet approach for fast multidimensional scaling. - Pierre Lambert; Cyril de Bodt; Michel Verleysen; John A. Lee 001 (ESANN, 2021)

Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding. - Pierre Lambert; John A. Lee 001; Michel Verleysen; Cyril de Bodt (ESANN, 2021)

Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models. - John A. Lee 001; Alyssa Vanginderdeuren; Margerie Huet-Dastarac; Ana Maria Barragán-Montero (ESANN, 2021)

Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT. - Eliott Brion; Jean Léger; Ana M. Barragan-Montero; Nicolas Meert; John A. Lee 001; Benoît Macq (Comput. Biol. Medicine, 2021)

Compressive lensless endoscopy with partial speckle scanning. - Stéphanie Guérit; Siddharth Sivankutty; John Aldo Lee; Hervé Rigneault; Laurent Jacques (CoRR, 2021)

Tuning Database-Friendly Random Projection Matrices for Improved Distance Preservation on Specific Data. - Daniel López Sánchez; Cyril de Bodt; John A. Lee 001; Angélica González Arrieta; Juan M. Corchado (Appl. Intell., 2022)

Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers. - Sophie Wuyckens; Michael Saint-Guillain; Guillaume Janssens; Lewei Zhao; Xiaoqiang Li; Xuanfeng Ding; Edmond Sterpin; John A. Lee 001; Kevin Souris (Comput. Biol. Medicine, 2022)

SQuadMDS: a lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP. - Pierre Lambert; Cyril de Bodt; Michel Verleysen; John A. Lee 001 (CoRR, 2022)

Deep learning to detect bacterial colonies for the production of vaccines. - Thomas Beznik; Paul Smyth; Gaël de Lannoy; John A. Lee 001 (Neurocomputing, 2022)

SQuadMDS: A lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP. - Pierre Lambert; Cyril de Bodt; Michel Verleysen; John A. Lee 001 (Neurocomputing, 2022)

Compressive Imaging Through Optical Fiber with Partial Speckle Scanning. - Stéphanie Guérit; Siddharth Sivankutty; John A. Lee 001; Hervé Rigneault; Laurent Jacques (SIAM J. Imaging Sci., 2022)

Fast Multiscale Neighbor Embedding. - Cyril de Bodt; Dounia Mulders; Michel Verleysen; John Aldo Lee (IEEE Trans. Neural Networks Learn. Syst., 2022)

Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer. - Ana Maria Barragán-Montero; Robin Tilman; Margerie Huet-Dastarac; John A. Lee 001 (ESANN, 2023)

On the number of latent representations in deep neural networks for tabular data. - Edouard Couplet; Pierre Lambert; Michel Verleysen; John A. Lee 001; Cyril de Bodt (ESANN, 2023)

Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration. - Pierre Lambert; John A. Lee 001; Edouard Couplet; Cyril de Bodt (ESANN, 2023)

Natively Interpretable t-SNE. - Edouard Couplet; Pierre Lambert; Michel Verleysen; Dounia Mulders; John A. Lee 001; Cyril de Bodt (PKDD/ECML Workshops (1), 2023)

Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? - Application to proton therapy dose prediction for head and neck cancer patients. - Margerie Huet-Dastarac; Dan Nguyen; Steve B. Jiang; John A. Lee 001; Ana M. Barragan-Montero (CoRR, 2023)

Semi-supervised t-SNE with multi-scale neighborhood preservation. - Walter Serna-Serna; Cyril de Bodt; Andrés Marino Álvarez-Meza; John A. Lee 001; Michel Verleysen; Álvaro-Ángel Orozco-Gutiérrez (Neurocomputing, 2023)

Forget early exaggeration in t-SNE: early hierarchization preserves global structure. - John A. Lee 001; Edouard Couplet; Pierre Lambert; Ludovic Journaux; Dounia Mulders; Cyril de Bodt; Michel Verleysen (ESANN, 2024)

Estimated neighbour sets and smoothed sampled global interactions are sufficient for a fast approximate tSNE. - Pierre Lambert; Edouard Couplet; Cyril de Bodt; John A. Lee 001 (ESANN, 2024)

SDE U-Net: Disentangling Aleatoric and Epistemic Uncertainties in Medical Image Segmentation. - Chuxin Zhang; Ana Maria Barragán-Montero; John A. Lee 001 (ESANN, 2024)

PARROT - A Versatile Platform for AI-Driven Image Segmentation and Dose Prediction. - Wei Zhao; Margerie Huet-Dastarac; Sylvain Deffet; Edmond Sterpin; Ana M. Barragan-Montero; Sébastien Jodogne; John A. Lee 001 (MICAD, 2024)

The proton arc therapy treatment planning problem is NP-Hard. - Viktor Wase; Sophie Wuyckens; John A. Lee 001; Michael Saint-Guillain (Comput. Biol. Medicine, 2024)

Investigating latent representations and generalization in deep neural networks for tabular data. - Edouard Couplet; Pierre Lambert; Michel Verleysen; John A. Lee 001; Cyril de Bodt (Neurocomputing, 2024)