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Neural Field Model for Measuring and Reproducing Time Intervals.

, , , and . ICANN (1), volume 11727 of Lecture Notes in Computer Science, page 327-338. Springer, (2019)

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The power of prediction: Robots that read intentions., , , , , , , , , and 7 other author(s). IROS, page 5458-5459. IEEE, (2012)Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait., , , , , , , , , and . BIBM, page 2024-2030. IEEE Computer Society, (2018)Towards temporal cognition for robots: A neurodynamics approach., , , , and . ICDL-EPIROB, page 407-412. IEEE, (2017)Towards Endowing Collaborative Robots with Fast Learning for Minimizing Tutors' Demonstrations: What and When to Do?, , , , , , , and . ROBOT (1), volume 1092 of Advances in Intelligent Systems and Computing, page 368-378. Springer, (2019)Neural Field Model for Measuring and Reproducing Time Intervals., , , and . ICANN (1), volume 11727 of Lecture Notes in Computer Science, page 327-338. Springer, (2019)Off-line simulation inspires insight: A neurodynamics approach to efficient robot task learning., , , and . Neural Networks, (2015)Learning a musical sequence by observation: A robotics implementation of a dynamic neural field model., , , , and . ICDL-EPIROB, page 157-162. IEEE, (2014)Learning joint representations for order and timing of perceptual-motor sequences: A dynamic neural field approach., , , and . IJCNN, page 1-7. IEEE, (2015)A Dynamic Field Model of Ordinal and Timing Properties of Sequential Events., , and . ICANN (2), volume 6792 of Lecture Notes in Computer Science, page 325-332. Springer, (2011)