87 citations · 156 across the 13 of their papers we have counts for
13 papers
On Syntactical Simplification of Temporal Operators in Negation-free MTL
Mathijs van Noort, Femke Ongenae, Pieter Bonte
Temporal reasoning in dynamic, data-intensive environments increasingly demands expressive yet tractable logical frameworks. Traditional approaches often rely on negation to expres…
From Haystack to Needle: Label Space Reduction for Zero-shot Classification
Nathan Vandemoortele, Bram Steenwinckel, Femke Ongenae +1
We present Label Space Reduction (LSR), a novel method for improving zero-shot classification performance of Large Language Models (LLMs). LSR iteratively refines the classificatio…
RDF Surfaces: Enabling Classical Negation on the Semantic Web
Patrick Hochstenbach, Mathijs van Noort, Dörthe Arndt +5
The Resource Description Framework (RDF) is a fundamental technology in the Semantic Web, enabling the representation and interchange of structured data. However, RDF lacks the cap…
Addressing Data Quality Challenges in Observational Ambulatory Studies: Analysis, Methodologies and Practical Solutions for Wrist-worn Wearable Monitoring
Jonas Van Der Donckt, Nicolas Vandenbussche, Jeroen Van Der Donckt +7
Chronic disease management and follow-up are vital for realizing sustained patient well-being and optimal health outcomes. Recent advancements in wearable sensing technologies, par…
Perfectly predicting ICU length of stay: too good to be true
Sandeep Ramachandra, Gilles Vandewiele, David Vander Mijnsbrugge +2
A paper of Alsinglawi et al was recently accepted and published in Scientific Reports. In this paper, the authors aim to predict length of stay (LOS), discretized into either long…
Powershap: A Power-full Shapley Feature Selection Method
Jarne Verhaeghe, Jeroen Van Der Donckt, Femke Ongenae +1
Feature selection is a crucial step in developing robust and powerful machine learning models. Feature selection techniques can be divided into two categories: filter and wrapper m…
pyRDF2Vec: A Python Implementation and Extension of RDF2Vec
Gilles Vandewiele, Bram Steenwinckel, Terencio Agozzino +1
This paper introduces pyRDF2Vec, a Python software package that reimplements the well-known RDF2Vec algorithm along with several of its extensions. By making the algorithm availabl…
R-GCN: The R Could Stand for Random
Vic Degraeve, Gilles Vandewiele, Femke Ongenae +1
The inception of the Relational Graph Convolutional Network (R-GCN) marked a milestone in the Semantic Web domain as a widely cited method that generalises end-to-end hierarchical…
Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs
Gilles Vandewiele, Bram Steenwinckel, Pieter Bonte +5
As KGs are symbolic constructs, specialized techniques have to be applied in order to make them compatible with data mining techniques. RDF2Vec is an unsupervised technique that ca…
Overly Optimistic Prediction Results on Imbalanced Data: a Case Study of Flaws and Benefits when Applying Over-sampling
Gilles Vandewiele, Isabelle Dehaene, György Kovács +9
Information extracted from electrohysterography recordings could potentially prove to be an interesting additional source of information to estimate the risk on preterm birth. Rece…
GENDIS: GENetic DIscovery of Shapelets
Gilles Vandewiele, Femke Ongenae, Filip De Turck
In the time series classification domain, shapelets are small time series that are discriminative for a certain class. It has been shown that classifiers are able to achieve state-…
Positive blood culture detection in time series data using a BiLSTM network
Leen De Baets, Joeri Ruyssinck, Thomas Peiffer +4
The presence of bacteria or fungi in the bloodstream of patients is abnormal and can lead to life-threatening conditions. A computational model based on a bidirectional long short-…
GENESIM: genetic extraction of a single, interpretable model
Gilles Vandewiele, Olivier Janssens, Femke Ongenae +2
Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensembl…