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Jesper van Engelen
Jesper van Engelen
Autonomous Vehicles at NVIDIA, previously Leiden University and ETH Zürich
Verified email at liacs.nl
Title
Cited by
Cited by
Year
A survey on semi-supervised learning
JE Van Engelen, HH Hoos
Machine learning 109 (2), 373-440, 2020
27072020
The NVIDIA PilotNet experiments
M Bojarski, C Chen, J Daw, A Değirmenci, J Deri, B Firner, B Flepp, ...
arXiv preprint arXiv:2010.08776, 2020
342020
Explainable and efficient link prediction in real-world network data
JE van Engelen, HD Boekhout, FW Takes
Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA …, 2016
202016
Successive statistical and structure-based modeling to identify chemically novel kinase inhibitors
L Burggraaff, EB Lenselink, W Jespers, J van Engelen, BJ Bongers, ...
Journal of Chemical Information and Modeling 60 (9), 4283-4295, 2020
82020
Accurate WiFi-based Indoor Positioning with Continuous Location Sampling
JE van Engelen, JJ van Lier, FW Takes, H Trautmann
62018
Guided rewriting in families of languages
JE van Engelen
Technical Report 2012–2013–12, LIACS, 2013
42013
Training configuration-agnostic machine learning models using synthetic data for autonomous machine applications
A Degirmenci, H Won, M Bojarski, JE Van Engelen, B Firner, Z Yang, ...
US Patent App. 17/497,479, 2023
32023
Semi-supervised co-ensembling for automl
JE van Engelen, HH Hoos
Trustworthy AI-Integrating Learning, Optimization and Reasoning: First …, 2021
22021
Semi-supervised Ensemble Learning
JE van Engelen
Leiden Institute of Advanced Computer Science, 2018
2018
Chapter five Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors
L Burggraaff, EB Lenselink, W Jespers, J van Engelen, BJ Bongers
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Articles 1–10