| Multimodal integration learning of robot behavior using deep neural networks K Noda, H Arie, Y Suga, T Ogata Robotics and Autonomous Systems 62 (6), 721-736, 2014 | 232 | 2014 |
| Learning to reproduce fluctuating time series by inferring their time-dependent stochastic properties: Application in robot learning via tutoring S Murata, J Namikawa, H Arie, S Sugano, J Tani IEEE Transactions on Autonomous Mental Development 5 (4), 298-310, 2013 | 89 | 2013 |
| Learning to perceive the world as probabilistic or deterministic via interaction with others: A neuro-robotics experiment S Murata, Y Yamashita, H Arie, T Ogata, S Sugano, J Tani IEEE transactions on neural networks and learning systems 28 (4), 830-848, 2015 | 60 | 2015 |
| Emergence of hierarchical structure mirroring linguistic composition in a recurrent neural network W Hinoshita, H Arie, J Tani, HG Okuno, T Ogata Neural Networks 24 (4), 311-320, 2011 | 50 | 2011 |
| Dynamical integration of language and behavior in a recurrent neural network for human–robot interaction T Yamada, S Murata, H Arie, T Ogata Frontiers in neurorobotics 10, 5, 2016 | 47 | 2016 |
| Hyperbolic positioning with antenna arrays and multi-channel pseudolite for indoor localization K Fujii, Y Sakamoto, W Wang, H Arie, A Schmitz, S Sugano Sensors 15 (10), 25157-25175, 2015 | 39 | 2015 |
| Imitating others by composition of primitive actions: A neuro-dynamic model H Arie, T Arakaki, S Sugano, J Tani Robotics and Autonomous Systems 60 (5), 729-741, 2012 | 33 | 2012 |
| Creating novel goal-directed actions at criticality: A neuro-robotic experiment H Arie, T Endo, T Arakaki, S Sugano, J Tani New Mathematics and Natural Computation 5 (01), 307-334, 2009 | 31 | 2009 |
| Neuro-robotics study on integrative learning of proactive visual attention and motor behaviors S Jeong, H Arie, M Lee, J Tani Cognitive neurodynamics 6, 43-59, 2012 | 25 | 2012 |
| Multimodal integration learning of object manipulation behaviors using deep neural networks K Noda, H Arie, Y Suga, T Ogata 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 22 | 2013 |
| Learning to achieve different levels of adaptability for human–robot collaboration utilizing a neuro-dynamical system S Murata, Y Li, H Arie, T Ogata, S Sugano IEEE Transactions on Cognitive and Developmental Systems 10 (3), 712-725, 2018 | 20 | 2018 |
| Synthetic approach to understanding meta-level cognition of predictability in generating cooperative behavior J Namikawa, R Nishimoto, H Arie, J Tani Advances in Cognitive Neurodynamics (III) Proceedings of the Third …, 2013 | 19 | 2013 |
| Reinforcement learning of a continuous motor sequence with hidden states H Arie, T Ogata, J Tani, S Sugano Advanced Robotics 21 (10), 1215-1229, 2007 | 19 | 2007 |
| Sensor prediction and grasp stability evaluation for in-hand manipulation K Kojima, T Sato, A Schmitz, H Arie, H Iwata, S Sugano 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 18 | 2013 |
| Representation learning of logic words by an RNN: from word sequences to robot actions T Yamada, S Murata, H Arie, T Ogata Frontiers in neurorobotics 11, 70, 2017 | 17 | 2017 |
| Emergence of interactive behaviors between two robots by prediction error minimization mechanism Y Chen, S Murata, H Arie, T Ogata, J Tani, S Sugano 2016 Joint IEEE International Conference on Development and Learning and …, 2016 | 15 | 2016 |
| Integrative learning between language and action: A neuro-robotics experiment H Arie, T Endo, S Jeong, M Lee, S Sugano, J Tani Artificial Neural Networks–ICANN 2010: 20th International Conference …, 2010 | 15 | 2010 |
| High-accuracy IMES localization using a movable receiver antenna and a three-axis attitude sensor Y Sakamoto, H Arie, T Ebinuma, K Fujii, S Sugano 2011 International Conference on Indoor Positioning and Indoor Navigation, 1-6, 2011 | 14 | 2011 |
| Achieving human–robot collaboration with dynamic goal inference by gradient descent S Murata, W Masuda, J Chen, H Arie, T Ogata, S Sugano Neural Information Processing: 26th International Conference, ICONIP 2019 …, 2019 | 12 | 2019 |
| Learning to generate proactive and reactive behavior using a dynamic neural network model with time-varying variance prediction mechanism S Murata, H Arie, T Ogata, S Sugano, J Tani Advanced Robotics 28 (17), 1189-1203, 2014 | 12 | 2014 |
Tetsuya OgataProfessor, Waseda University / Joint-appointed Fellow, AISTVerifisert e-postadresse på waseda.jp
