Gilles Vandewiele

According to our database1, Gilles Vandewiele authored at least 29 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Do not sleep on traditional machine learning: Simple and interpretable techniques are competitive to deep learning for sleep scoring.
Biomed. Signal Process. Control., March, 2023

REFORMS: Reporting Standards for Machine Learning Based Science.
CoRR, 2023

pyRDF2Vec: A Python Implementation and Extension of RDF2Vec.
Proceedings of the Semantic Web - 20th International Conference, 2023

Deep learning models for predicting RNA degradation via dual crowdsourcing.
Nat. Mac. Intell., December, 2022

INK: knowledge graph embeddings for node classification.
Data Min. Knowl. Discov., 2022

Perfectly predicting ICU length of stay: too good to be true.
CoRR, 2022

Do Not Sleep on Linear Models: Simple and Interpretable Techniques Outperform Deep Learning for Sleep Scoring.
CoRR, 2022

R-GCN: The R Could Stand for Random.
CoRR, 2022

GENDIS: Genetic Discovery of Shapelets.
Sensors, 2021

Predictive models of RNA degradation through dual crowdsourcing.
CoRR, 2021

Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling.
Artif. Intell. Medicine, 2021

Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs.
Proceedings of the Database and Expert Systems Applications - DEXA 2021 Workshops, 2021

MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph.
BMC Medical Informatics Decis. Mak., 2020

Tslearn, A Machine Learning Toolkit for Time Series Data.
J. Mach. Learn. Res., 2020

Clinical information extraction for preterm birth risk prediction.
J. Biomed. Informatics, 2020

Overly Optimistic Prediction Results on Imbalanced Data: Flaws and Benefits of Applying Over-sampling.
CoRR, 2020

Facilitating the Analysis of COVID-19 Literature Through a Knowledge Graph.
Proceedings of the Semantic Web - ISWC 2020, 2020

How do Users interact with Mobile Health Apps?: A Markov Chain Analysis.
Proceedings of the PervasiveHealth '20: 14th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2020

CVS2KG: Transforming Tabular Data into Semantic Knowledge.
Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching co-located with the 18th International Semantic Web Conference, 2019

Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph.
Proceedings of the 4th International Workshop on Semantics-Powered Data Mining and Analytics co-located with the 18th International Semantic Web Conference (ISWC 2019), 2019

A Critical Look at Studies Applying Over-Sampling on the TPEHGDB Dataset.
Proceedings of the Artificial Intelligence in Medicine, 2019

Time-to-Birth Prediction Models and the Influence of Expert Opinions.
Proceedings of the Artificial Intelligence in Medicine, 2019

A decision support system to follow up and diagnose primary headache patients using semantically enriched data.
BMC Medical Informatics Decis. Mak., 2018

Predicting Train Occupancies based on Query Logs and External Data Sources.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Enabling Training Personalization by Predicting the Sessioon Rate of Perceived Exertion.
Proceedings of the 4th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017

A Genetic Algorithm for Interpretable Model Extraction from Decision Tree Ensembles.
Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2017

Real-Time data dissemination and analytics platform for challenging IoT environments.
Proceedings of the 2017 Global Information Infrastructure and Networking Symposium, 2017

Enhancing White-Box Machine Learning Processes by Incorporating Semantic Background Knowledge.
Proceedings of the Semantic Web - 14th International Conference, 2017

GENESIM: genetic extraction of a single, interpretable model.
CoRR, 2016