87 citations · 216 across the 10 of their papers we have counts for
10 papers
REFORMS: Reporting Standards for Machine Learning Based Science
Sayash Kapoor, Emily Cantrell, Kenny Peng +16
Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and ge…
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…
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring
Jeroen Van Der Donckt, Jonas Van Der Donckt, Emiel Deprost +4
Over the last few years, research in automatic sleep scoring has mainly focused on developing increasingly complex deep learning architectures. However, recently these approaches a…
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…
Deep learning models for predicting RNA degradation via dual crowdsourcing
Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins +26
Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limite…
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-…
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…