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# Reinforcement Learning
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# Machine Learning
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Publicaties
Recent
Schulte, R. V. (2022).
Up to one's knees in data: Data-driven intent recognition using electromyography for the lower limb. [PhD Thesis - Research external, graduation UT, University of Twente]. University of Twente.
https://doi.org/10.3990/1.9789036554862
Schulte, R. V.
, Prinsen, E. C.
, Buurke, J. H.
, & Poel, M. (2022).
Adaptive Lower Limb Pattern Recognition for Multi-Day Control.
Sensors,
22(17), [6351].
https://doi.org/10.3390/s22176351
Verma, D., Jansen, D., Bach, K.
, Poel, M., Mork, P. J.
, & d'Hollosy, W. (2022).
Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes.
BMC medical informatics and decision making,
22, [227].
https://doi.org/10.1186/s12911-022-01973-9
Botteghi, N., Grefte, L.
, Poel, M.
, Sirmacek, B.
, Brune, C.
, Dertien, E.
, & Stramigioli, S. (2022).
Towards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning. In J. Kim, B. Englot, H-W. Park, H-L. Choi, H. Myung, J. Kim, & J-H. Kim (Eds.),
Robot Intelligence Technology and Applications 6 - Results from the 9th International Conference on Robot Intelligence Technology and Applications (pp. 259-271). (Lecture Notes in Networks and Systems; Vol. 429 LNNS). Springer Science + Business Media.
https://doi.org/10.1007/978-3-030-97672-9_23
de With, L. A.
, Thammasan, N.
, & Poel, M. (2022).
Detecting Fear of Heights Response to a Virtual Reality Environment Using Functional Near-Infrared Spectroscopy.
Frontiers in Computer Science,
3, [652550].
https://doi.org/10.3389/fcomp.2021.652550
Botteghi, N.
, Sirmacek, B.
, Poel, M.
, Brune, C., & Schulte, R. (2021).
CURIOSITY-DRIVEN REINFORCEMENT LEARNING AGENT for MAPPING UNKNOWN INDOOR ENVIRONMENTS.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences,
5(1), 129-136.
https://doi.org/10.5194/isprs-annals-V-1-2021-129-2021
Botteghi, N., Alaa, K.
, Poel, M.
, Sirmaçek, B.
, Brune, C., Mersha, A.
, & Stramigioli, S. (2021).
Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces. In
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 (pp. 190-197). (IEEE International Conference on Intelligent Robots and Systems). IEEE.
https://doi.org/10.1109/IROS51168.2021.9635936
Botteghi, N. (2021).
Robotics deep reinforcement learning with loose prior knowledge. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente.
https://doi.org/10.3990/1.9789036552165
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Master
Vakken Collegejaar 2022/2023
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
Vakken Collegejaar 2021/2022
Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(gebouwnr. 11), kamer 4102
Hallenweg 19
7522NH Enschede
Postadres
Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4102
Postbus 217
7500 AE Enschede