| A survey on semi-supervised learning JE Van Engelen, HH Hoos Machine learning 109 (2), 373-440, 2020 | 2488 | 2020 |
| The NVIDIA PilotNet experiments M Bojarski, C Chen, J Daw, A Değirmenci, J Deri, B Firner, B Flepp, ... arXiv preprint arXiv:2010.08776, 2020 | 31 | 2020 |
| 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 | 19 | 2016 |
| 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 | 7 | 2020 |
| Accurate WiFi-based Indoor Positioning with Continuous Location Sampling JE van Engelen, JJ van Lier, FW Takes, H Trautmann | 6 | 2018 |
| 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 | 4 | 2023 |
| Guided rewriting in families of languages JE van Engelen Technical Report 2012–2013–12, LIACS, 2013 | 3 | 2013 |
| Semi-supervised co-ensembling for automl JE van Engelen, HH Hoos Trustworthy AI-Integrating Learning, Optimization and Reasoning: First …, 2021 | 2 | 2021 |
| 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 | | |
