Search Results for author: Yvan Saeys

Found 16 papers, 7 papers with code

GroupEnc: encoder with group loss for global structure preservation

no code implementations6 Sep 2023 David Novak, Sofie Van Gassen, Yvan Saeys

Recent advances in dimensionality reduction have achieved more accurate lower-dimensional embeddings of high-dimensional data.

Clustering Community Detection +1

Topologically Regularized Data Embeddings

1 code implementation9 Jan 2023 Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt

In some cases, users may have prior topological knowledge about the data, such as a known cluster structure or the fact that the data is known to lie along a tree- or graph-structured topology.

Computational Efficiency Dimensionality Reduction +2

Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems

no code implementations7 Sep 2022 Arne Gevaert, Jonathan Peck, Yvan Saeys

In this work, we present an algorithm to distill the policy from a deep Q-network into a compact neuro-fuzzy controller.

OpenAI Gym reinforcement-learning +1

PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition

no code implementations26 Aug 2022 Arne Gevaert, Yvan Saeys

Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models.

Evaluating Feature Attribution Methods in the Image Domain

1 code implementation22 Feb 2022 Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys

Feature attribution maps are a popular approach to highlight the most important pixels in an image for a given prediction of a model.

Benchmarking

Topologically Regularized Data Embeddings

1 code implementation ICLR 2022 Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys

For tasks for which prior expert topological knowledge is available, incorporating this into the learned representation may lead to higher quality embeddings.

Graph Embedding Representation Learning

The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?

1 code implementation22 Sep 2021 Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys

Previously, it has been argued that neighborhood queries become meaningless and unstable when distance concentration occurs, which means that there is a poor relative discrimination between the furthest and closest neighbors in the data.

Dimensionality Reduction Representation Learning

Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability

1 code implementation7 Jul 2020 Utku Ozbulak, Jonathan Peck, Wesley De Neve, Bart Goossens, Yvan Saeys, Arnout Van Messem

Regional adversarial attacks often rely on complicated methods for generating adversarial perturbations, making it hard to compare their efficacy against well-known attacks.

Cost-efficient segmentation of electron microscopy images using active learning

no code implementations13 Nov 2019 Joris Roels, Yvan Saeys

Our experiments on three different electron microscopy datasets show that active learning can improve segmentation quality by 10 to 15% in terms of Jaccard score compared to standard randomized sampling.

Active Learning Image Classification +3

Essential guidelines for computational method benchmarking

1 code implementation3 Dec 2018 Lukas M. Weber, Wouter Saelens, Robrecht Cannoodt, Charlotte Soneson, Alexander Hapfelmeier, Paul Gardner, Anne-Laure Boulesteix, Yvan Saeys, Mark D. Robinson

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses.

Benchmarking

Domain Adaptive Segmentation in Volume Electron Microscopy Imaging

1 code implementation23 Oct 2018 Joris Roels, Julian Hennies, Yvan Saeys, Wilfried Philips, Anna Kreshuk

In this work, we extend recently proposed classification DA techniques to an encoder-decoder layout and propose a novel method that adds a reconstruction decoder to the classical encoder-decoder segmentation in order to align source and target encoder features.

Classification Domain Adaptation +2

Interpretable Convolutional Neural Networks for Effective Translation Initiation Site Prediction

no code implementations27 Nov 2017 Jasper Zuallaert, Mijung Kim, Yvan Saeys, Wesley De Neve

Thanks to rapidly evolving sequencing techniques, the amount of genomic data at our disposal is growing increasingly large.

Decision Making Translation

On the use of convolutional neural networks for robust classification of multiple fingerprint captures

no code implementations21 Mar 2017 Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, Jose M. Benitez, Francisco Herrera

In our experiments, convolutional neural networks yielded better accuracy and penetration rate than state-of-the-art classifiers based on explicit feature extraction.

Classification General Classification +1

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