Timothy Verstraeten
Timothy Verstraeten
PhD Researcher in Computer Science, Vrije Universiteit Brussel
Verified email at vub.ac.be
TitleCited byYear
Bayesian best-arm identification for selecting influenza mitigation strategies
PJK Libin, T Verstraeten, DM Roijers, J Grujic, K Theys, P Lemey, A Now
Joint European Conference on Machine Learning and Knowledge Discovery in…, 2018
62018
Learning to coordinate with coordination graphs in repeated single-stage multi-agent decision problems
E Bargiacchi, T Verstraeten, D Roijers, A Now, H Hasselt
International conference on machine learning, 482-490, 2018
52018
Efficient evaluation of influenza mitigation strategies using preventive bandits
P Libin, T Verstraeten, K Theys, DM Roijers, P Vrancx, A Now
International Conference on Autonomous Agents and Multiagent Systems, 67-85, 2017
42017
Fleetwide data-enabled reliability improvement of wind turbines
T Verstraeten, A Nowe, J Keller, Y Guo, S Sheng, J Helsen
Renewable and Sustainable Energy Reviews 109, 428-437, 2019
22019
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers
FG Marulanda, P Libin, T Verstraeten, A Now
2018 IEEE 30th International Conference on Tools with Artificial…, 2018
22018
Reinforcement learning for fleet applications using coregionalized gaussian processes
T Verstraeten, A Now
Adaptive Learning Agents (ALA) Workshop at AAMAS). IFAAMAS 57, 2018
22018
Fleet-wide condition monitoring combining vibration signal processing and machine learning rolled out in a cloud-computing environment
J Helsen, C Peeters, T Verstraeten, J Verbeke, N Gioia, A Now
International Conference on Noise and Vibration Engineering (ISMA), 2018
12018
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping
E Bargiacchi, T Verstraeten, DM Roijers, A Now
arXiv preprint arXiv:2001.07527, 2020
2020
Combining Machine Learning and Operational Modal Analysis Approaches to Gain Insights in Wind Turbine Drivetrain Dynamics
N Gioia, PJ Daems, T Verstraeten, P Guillaume, J Helsen
Topics in Modal Analysis & Testing, Volume 8, 293-299, 2020
2020
Advanced Vibration Signal Processing Using Edge Computing to Monitor Wind Turbine Drivetrains
C Peeters, T Verstraeten, A Now, PJ Daems, J Helsen
ASME 2019 2nd International Offshore Wind Technical Conference, 2019
2019
Thompson Sampling for Factored Multi-Agent Bandits
T Verstraeten, E Bargiacchi, PJK Libin, DM Roijers, A Now
arXiv preprint arXiv:1911.10120, 2019
2019
Fleet Control using Coregionalized Gaussian Process Policy Iteration
T Verstraeten, PJK Libin, A Now
arXiv preprint arXiv:1911.10121, 2019
2019
Bayesian Anytime m-top Exploration
P Libin, T Verstraeten, DM Roijers, W Wang, K Theys, A Nowe
2019 IEEE 31st International Conference on Tools with Artificial…, 2019
2019
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers
F Gomez Marulanda, P Libin, T Verstraeten, A Now
arXiv preprint arXiv:1909.13726, 2019
2019
Edge computing for advanced vibration signal processing
T Verstraeten, FG Marulanda, C Peeters, PJ Daems, A Now, J Helsen
2019
Drivetrain reliability improvements from long-term field data processed in the cloud
C Peeters, N Gioia, PJ Daems, J Verbeke, T Verstraeten, A Now, ...
Journal of Physics: Conference Series 1222 (1), 012044, 2019
2019
Deep hybrid approach for 3D plane segmentation
FG Marulanda, P Libin, T Verstraeten, A Now
ESANN 2019, 2019
2019
Privacy Preserving Reinforcement Learning over Distributed Datasets
R Loeb, T Verstraeten, A Nowe, A Dooms
2019
Combining Edge and Cloud Computing for Monitoring a Fleet of Wind Turbine Drivetrains Using Combined Machine Learning Signal Processing Approaches
C PEETERS, PJ DAEMS, T VERSTRAETEN, A NOW, J HELSEN
Structural Health Monitoring 2019, 2019
2019
Thompson sampling for m-top Exploration
P Libin, T Verstraeten, DM Roijers, W Wang, K Theys, A Now
2019
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