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Thibaut Kulak
Thibaut Kulak
NeoInstinct SA
Verified email at neoinstinct.com
Title
Cited by
Cited by
Year
Fourier movement primitives: an approach for learning rhythmic robot skills from demonstrations.
T Kulak, J Silvério, S Calinon
Robotics: Science and systems, 2020
162020
Active learning of Bayesian probabilistic movement primitives
T Kulak, H Girgin, JM Odobez, S Calinon
IEEE Robotics and Automation Letters 6 (2), 2163-2170, 2021
112021
Combining Social and Intrinsically Motivated Learning for Multitask Robot Skill Acquisition
T Kulak, S Calinon
IEEE Transactions on Cognitive and Developmental Systems 15 (2), 385-394, 2021
22021
Representation learning in partially observable environments using sensorimotor prediction
T Kulak, MG Ortiz
arXiv preprint arXiv:1803.00268, 2018
12018
A Unified View on Self-Organizing Maps (SOMs) and Stochastic Neighbor Embedding (SNE)
T Kulak, A Fillion, F Blayo
International Conference on Artificial Neural Networks, 458-468, 2022
2022
A Bayesian Variational principle for dynamic Self Organizing Maps
A Fillion, T Kulak, F Blayo
arXiv preprint arXiv:2208.11337, 2022
2022
Learning strategies and representations for intuitive robot learning from demonstration
TA Kulak
EPFL, 2021
2021
Emergence of Sensory Representations Using Prediction in Partially Observable Environments
T Kulak, MG Ortiz
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
2018
SPECIAL ISSUE ON INTRINSICALLY MOTIVATED OPEN-ENDED LEARNING (IMOL)
K Kasmarik, G Baldassarre, VG Santucci, J Triesch, MI Sener, Y Nagai, ...
Intrinsically-Motivated Robot Learning of Bayesian Probabilistic Movement Primitives
T Kulak, S Calinon
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