Jun Namikawa

发表

Learning to segment temporal sequences by mixture of RNN experts with adaptive variance model

Jun Tani, Jun Namikawa, 2007 .

A model for learning to segment temporal sequences, utilizing a mixture of RNN experts together with adaptive variance

Jun Tani, Jun Namikawa, J. Tani, 2007, Neural Networks.

Learning to reproduce fluctuating behavioral sequences using a dynamic neural network model with time-varying variance estimation mechanism

Shigeki Sugano, Hiroaki Arie, Jun Tani, 2013, 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL).

An artificial network model for estimating the network structure underlying partially observed neuronal signals

Jun Tani, Misako Komatsu, Zenas C. Chao, 2014, Neuroscience Research.

Building Recurrent Neural Networks to Implement Multiple Attractor Dynamics Using the Gradient Descent Method

Jun Tani, Jun Namikawa, J. Tani, 2009, Adv. Artif. Neural Syst..

Learning to imitate stochastic time series in a compositional way by chaos

Jun Tani, Jun Namikawa, J. Tani, 2008, Neural Networks.

Learning to Reproduce Fluctuating Time Series by Inferring Their Time-Dependent Stochastic Properties: Application in Robot Learning Via Tutoring

Shigeki Sugano, Hiroaki Arie, Jun Tani, 2013, IEEE Transactions on Autonomous Mental Development.

Reinforcement Learning Algorithm with CTRNN in Continuous Action Space

Shigeki Sugano, Tetsuya Ogata, Hiroaki Arie, 2006, ICONIP.

Development of Proactive and Reactive Behavior via Meta-learning of Prediction Error Variance

Shigeki Sugano, Hiroaki Arie, Jun Tani, 2013, ICONIP.

Estimation of functional brain connectivity from electrocorticograms using an artificial network model

Naotaka Fujii, Jun Tani, Misako Komatsu, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Learning Multiple Goal-Directed Actions Through Self-Organization of a Dynamic Neural Network Model: A Humanoid Robot Experiment

Jun Tani, Jun Namikawa, Ryunosuke Nishimoto, 2008, Adapt. Behav..

Codevelopmental Learning Between Human and Humanoid Robot Using a Dynamic Neural-Network Model

Jun Tani, Masato Ito, Jun Namikawa, 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

A Neurodynamic Account of Spontaneous Behaviour

Jun Tani, Jun Namikawa, Ryunosuke Nishimoto, 2011, PLoS Comput. Biol..

Synthetic Approach to Understanding Meta-level Cognition of Predictability in Generating Cooperative Behavior

Hiroaki Arie, Jun Tani, Jun Namikawa, 2013 .

Chaotic itinerancy and power-law residence time distribution in stochastic dynamical systems.

Jun Namikawa, Jun Namikawa, 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.