John A. Lee

Orcid: 0000-0001-5218-759X

Affiliations:
  • Université catholique de Louvain, Belgium


According to our database1, John A. Lee authored at least 104 papers between 2000 and 2023.

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Bibliography

2023
Semi-supervised <i>t</i>-SNE with multi-scale neighborhood preservation.
Neurocomputing, 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.
CoRR, 2023

2022
Fast Multiscale Neighbor Embedding.
IEEE Trans. Neural Networks Learn. Syst., 2022

Compressive Imaging Through Optical Fiber with Partial Speckle Scanning.
SIAM J. Imaging Sci., 2022

SQuadMDS: A lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like <i>t</i>-SNE and UMAP.
Neurocomputing, 2022

Deep learning to detect bacterial colonies for the production of vaccines.
Neurocomputing, 2022

SQuadMDS: a lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP.
CoRR, 2022

Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers.
Comput. Biol. Medicine, 2022

Tuning Database-Friendly Random Projection Matrices for Improved Distance Preservation on Specific Data.
Appl. Intell., 2022

2021
Compressive lensless endoscopy with partial speckle scanning.
CoRR, 2021

Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT.
Comput. Biol. Medicine, 2021

Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Stochastic quartet approach for fast multidimensional scaling.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
Perplexity-free Parametric t-SNE.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019
Nonlinear Dimensionality Reduction With Missing Data Using Parametric Multiple Imputations.
IEEE Trans. Neural Networks Learn. Syst., 2019

Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Using planning CTs to enhance CNN-based bladder segmentation on cone beam CT.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019

Tensor factorization to extract patterns in multimodal EEG data.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Class-aware t-SNE: cat-SNE.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018
A novel method for network intrusion detection based on nonlinear SNE and SVM.
Int. J. Artif. Intell. Soft Comput., 2018

Compressive Sampling Approach for Image Acquisition with Lensless Endoscope.
CoRR, 2018

Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks.
CoRR, 2018

Capturing variabilities from Computed Tomography images with Generative Adversarial Networks (GANs).
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Information visualisation and machine learning: latest trends towards convergence.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Extensive assessment of Barnes-Hut t-SNE.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Perplexity-free t-SNE and twice Student tt-SNE.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Contour Propagation in CT Scans with Convolutional Neural Networks.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2018

Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2018

2017
Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis.
IEEE Trans. Vis. Comput. Graph., 2017

What you see is what you can change: Human-centered machine learning by interactive visualization.
Neurocomputing, 2017

Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity.
Neurocomputing, 2017

Comparing dynamics of fluency and inter-limb coordination in climbing activities using multi-scale Jensen-Shannon embedding and clustering.
Data Min. Knowl. Discov., 2017

Large-scale nonlinear dimensionality reduction for network intrusion detection.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
Blind Deconvolution of PET Images using Anatomical Priors.
CoRR, 2016

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16).
CoRR, 2016

Multi-step-ahead forecasting using kernel adaptive filtering.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Image deconvolution by local order preservation of pixels values.
Proceedings of the 24th European Signal Processing Conference, 2016

Human-centered machine learning through interactive visualization: review and open challenges.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure.
Neurocomputing, 2015

Incremental classification of objects in scenes: Application to the delineation of images.
Neurocomputing, 2015

Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding.
Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), 2015

Post-reconstruction deconvolution of PET images by total generalized variation regularization.
Proceedings of the 23rd European Signal Processing Conference, 2015

Geometrical homotopy for data visualization.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Unsupervised dimensionality reduction: the challenge of big data visualization.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013).
Neurocomputing, 2014

Short Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Unsupervised Relevance Analysis for Feature Extraction and Selection - A Distance-based Approach for Feature Relevance.
Proceedings of the ICPRAM 2014, 2014

Recent methods for dimensionality reduction: A brief comparative analysis.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Generalized kernel framework for unsupervised spectral methods of dimensionality reduction.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Two key properties of dimensionality reduction methods.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013
Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation.
Neurocomputing, 2013

Stability Comparison of Dimensionality Reduction Techniques Attending to Data and Parameter Variations.
Proceedings of the 1st International Workshop on Visual Analytics Using Multidimensional Projections, 2013

Improving projection-based data analysis by feature space transformations.
Proceedings of the Visualization and Data Analysis 2013, 2013

Nonlinear Dimensionality Reduction for Visualization.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Segmentation with Incremental Classifiers.
Proceedings of the Image Analysis and Processing - ICIAP 2013, 2013

Sensitivity to parameter and data variations in dimensionality reduction techniques.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy.
IEEE Trans. Medical Imaging, 2012

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011).
Neurocomputing, 2012

Type 1 and 2 symmetric divergences for stochastic neighbor embedding.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Incremental feature building and classification for image segmentation.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants.
Proceedings of the International Conference on Computational Science, 2011

Advances in artificial neural networks, machine learning, and computational intelligence.
Neurocomputing, 2011

Mode estimation in high-dimensional spaces with flat-top kernels: Application to image denoising.
Neurocomputing, 2011

2010
Scale-independent quality criteria for dimensionality reduction.
Pattern Recognit. Lett., 2010

A principled approach to image denoising with similarity kernels involving patches.
Neurocomputing, 2010

Advances in computational intelligence and learning (ESANN 2009).
Neurocomputing, 2010

Dimensionality reduction by rank preservation.
Proceedings of the International Joint Conference on Neural Networks, 2010

Unsupervised dimensionality reduction: Overview and recent advances.
Proceedings of the International Joint Conference on Neural Networks, 2010

Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding.
Proceedings of the 19th International Conference on Computational Statistics, 2010

2009
Quality assessment of dimensionality reduction: Rank-based criteria.
Neurocomputing, 2009

Simbed: Similarity-Based Embedding.
Proceedings of the Artificial Neural Networks, 2009

Adaptive anisotropic denoising: a bootstrapped procedure.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Patch-based bilateral filter and local m-smoother for image denoising.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008
Edge-Preserving Filtering of Images with Low Photon Counts.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

Quality assessment of nonlinear dimensionality reduction based on K-ary neighborhoods.
Proceedings of the Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery, 2008

Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition.
Neurocomputing, 2008

Rank-based quality assessment of nonlinear dimensionality reduction.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007
A Minimum-Range Approach to Blind Extraction of Bounded Sources.
IEEE Trans. Neural Networks, 2007

Forecasting the CATS benchmark with the Double Vector Quantization method.
Neurocomputing, 2007

2006
Unfolding preprocessing for meaningful time series clustering.
Neural Networks, 2006

Non-orthogonal Support Width ICA.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

2005
Nonlinear dimensionality reduction of data manifolds with essential loops.
Neurocomputing, 2005

Filtering-Free Blind Separation of Correlated Images.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Can we always trust entropy minima in the ICA context?
Proceedings of the 13th European Signal Processing Conference, 2005

A simple ICA algorithm for non-differentiable contrasts.
Proceedings of the 13th European Signal Processing Conference, 2005

2004
Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis.
Neurocomputing, 2004

Non-linear ICA by Using Isometric Dimensionality Reduction.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

How to project 'circular' manifolds using geodesic distances?
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

2003
Analysis of high-dimensional numerical data: from principal component analysis to non-linear dimensionality reduction and blind source separation.
PhD thesis, 2003

Improving independent component analysis performances by variable selection.
Proceedings of the NNSP 2003, 2003

Locally Linear Embedding versus Isotop.
Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures.
Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002
Self-organizing maps with recursive neighborhood adaptation.
Neural Networks, 2002

Forecasting electricity consumption using nonlinear projection and self-organizing maps.
Neurocomputing, 2002

Nonlinear Projection with the Isotop Method.
Proceedings of the Artificial Neural Networks, 2002

Curvilinear Distance Analysis versus Isomap.
Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Width optimization of the Gaussian kernels in Radial Basis Function Networks.
Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

2001
Recursive learning rules for SOMs.
Proceedings of the Advances in Self-Organising Maps, 2001

Input data reduction for the prediction of financial time series.
Proceedings of the 9th European Symposium on Artificial Neural Networks, 2001

2000
Time series forecasting using CCA and Kohonen maps - application to electricity consumption.
Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000

A robust non-linear projection method.
Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000


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