Fourier movement primitives: an approach for learning rhythmic robot skills from demonstrations. T Kulak, J Silvério, S Calinon Robotics: Science and systems, 2020 | 16 | 2020 |
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 | 11 | 2021 |
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 | 2 | 2021 |
Representation learning in partially observable environments using sensorimotor prediction T Kulak, MG Ortiz arXiv preprint arXiv:1803.00268, 2018 | 1 | 2018 |
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 | | |