| Time series forecasting using a deep belief network with restricted Boltzmann machines T Kuremoto, S Kimura, K Kobayashi, M Obayashi Neurocomputing 137, 47-56, 2014 | 610 | 2014 |
| Time series forecasting using restricted Boltzmann machine T Kuremoto, S Kimura, K Kobayashi, M Obayashi Emerging Intelligent Computing Technology and Applications: 8th …, 2012 | 57 | 2012 |
| Time series prediction using DBN and ARIMA T Hirata, T Kuremoto, M Obayashi, S Mabu, K Kobayashi 2015 International Conference on Computer Application Technologies, 24-29, 2015 | 54 | 2015 |
| Forecast chaotic time series data by DBNs T Kuremoto, M Obayashi, K Kobayashi, T Hirata, S Mabu 2014 7th International Congress on Image and Signal Processing, 1130-1135, 2014 | 43 | 2014 |
| A wavelet neural network for function approximation and network optimization K Kobayashi, T Torioka Proceedings of ANNIE’94, AMSE Press, 505-510, 1994 | 23 | 1994 |
| Parameterless‐Growing‐SOM and Its Application to a Voice Instruction Learning System T Kuremoto, T Komoto, K Kobayashi, M Obayashi Journal of Robotics 2010 (1), 307293, 2010 | 22 | 2010 |
| Nonlinear prediction by reinforcement learning T Kuremoto, M Obayashi, K Kobayashi Advances in Intelligent Computing: International Conference on Intelligent …, 2005 | 22 | 2005 |
| Analyzing and learning an opponent’s strategies in the RoboCup small size league K Yasui, K Kobayashi, K Murakami, T Naruse RoboCup 2013: Robot World Cup XVII 17, 159-170, 2014 | 21 | 2014 |
| Adaptive swarm behavior acquisition by a neuro‐fuzzy system and reinforcement learning algorithm T Kuremoto, M Obayashi, K Kobayashi International journal of intelligent computing and cybernetics 2 (4), 724-744, 2009 | 21 | 2009 |
| A reinforcement learning system for swarm behaviors T Kuremoto, M Obayashi, K Kobayashi, H Adachi, K Yoneda 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008 | 20 | 2008 |
| A learning fuzzy Petri net model L Feng, M Obayashi, T Kuremoto, K Kobayashi IEEJ transactions on electrical and electronic engineering 7 (3), 274-282, 2012 | 19 | 2012 |
| A functional model of limbic system of brain T Kuremoto, T Ohta, K Kobayashi, M Obayashi International Conference on Brain Informatics, 135-146, 2009 | 17 | 2009 |
| A dynamic associative memory system by adopting an amygdala model T Kuremoto, T Ohta, K Kobayashi, M Obayashi Artificial Life and robotics 13, 478-482, 2009 | 17 | 2009 |
| A meta-learning method based on temporal difference error K Kobayashi, H Mizoue, T Kuremoto, M Obayashi Neural Information Processing: 16th International Conference, ICONIP 2009 …, 2009 | 17 | 2009 |
| Cooperative behavior acquisition in multi-agent reinforcement learning system using attention degree K Kobayashi, T Kurano, T Kuremoto, M Obayashi Neural Information Processing: 19th International Conference, ICONIP 2012 …, 2012 | 16 | 2012 |
| A gesture recognition system with retina-V1 model and one-pass dynamic programming T Kuremoto, Y Kinoshita, L Feng, S Watanabe, K Kobayashi, M Obayashi Neurocomputing 116, 291-300, 2013 | 15 | 2013 |
| A self-organized fuzzy-neuro reinforcement learning system for continuous state space for autonomous robots M Obayashi, T Kuremoto, K Kobayashi 2008 International Conference on Computational Intelligence for Modelling …, 2008 | 15 | 2008 |
| Neural forecasting systems T Kuremoto, M Obayashi, K Kobayashi Reinforcement Learning, 2008 | 15 | 2008 |
| Deep belief network using reinforcement learning and its applications to time series forecasting T Hirata, T Kuremoto, M Obayashi, S Mabu, K Kobayashi Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016 | 13 | 2016 |
| QoS optimization for web services composition based on reinforcement learning LB Feng, M Obayashi, T Kuremoto, K Kobayashi, S Watanabe Int. J. Innov. Comput., Inf. Control 9 (6), 2361-2376, 2013 | 13 | 2013 |
Takashi Kuremoto (呉本尭)Nippon Institute of Technology, ProfessorVerified email at nit.ac.jp
