Yu Terada

J-GLOBAL         Last updated: Jun 3, 2019 at 14:05
 
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Name
Yu Terada
E-mail
yu.teradariken.jp
Affiliation
RIKEN

Research Areas

 
 

Academic & Professional Experience

 
Apr 2018
 - 
Today
Special Postdoctoral Researcher, Center for Brain Science, Lab for Neural Computation and Adaption, RIKEN
 
Apr 2017
 - 
Mar 2018
Postdoctoral Researcher, Kabashima lab, Tokyo Institute of Technology
 

Education

 
Apr 2009
 - 
Mar 2012
Department of Physics, School of Science, Tokyo Institute of Technology
 
Apr 2014
 - 
Mar 2017
Graduate School of Informatics, Kyoto University
 
Apr 2012
 - 
Mar 2014
Graduate School of Informatics, Kyoto University
 
Apr 2008
 - 
Mar 2009
School of Life Science and Technology, Tokyo Institute of Technology
 

Published Papers

 
Terada Yu, Obuchi Tomoyuki, Isomura Takuya, Kabashima Yoshiyuki
Advances in Neural Information Processing Systems 31 (NeurIPS 2018)   4976-4985   Dec 2018   [Refereed]
Terada Yu, Ito Keigo, Aoyagi Toshio, Yamaguchi Yoshiyuki Y.
Journal of Statistical Mechanis: Theory and Experiment      Jan 2017   [Refereed]
Terada Yu, Aoyagi Toshio
Physical Review E   94(1)    Jul 2016   [Refereed]

Misc

 
Yu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima
   Mar 2018
Inferring directional connectivity from point process data of multiple
elements is desired in various scientific fields such as neuroscience,
geography, economics, etc. Here, we propose an inference procedure for this
goal based on the kinetic Isi...
Yu Terada, Keigo Ito, Ryosuke Yoneda, Toshio Aoyagi, Yoshiyuki Y. Yamaguchi
   Feb 2018
The linear response is studied in globally coupled oscillator systems
including the Kuramoto model. We develop a linear response theory which can be
applied to systems whose coupling functions are generic. Based on the theory,
we examine the role ...

Conference Activities & Talks

 
Dynamical mean field theory for coupled oscillators using the Plefka expansion
Yu Terada, Ivan Dacidovich, Yasser Roudi
74th Annual Meeting, The Physical Society of Japan   Mar 2019   
Estimation of neuronal couplings from multi-point activity data: how effective is the McCulloch-Pitts model for inference?
Yu Terada
Jul 2018   

Research Grants & Projects

 
Project Year: Apr 2019 - Mar 2022    Investigator(s): Yu Terada
Development of inference theory for phase oscillator models and understanding the way of information processing in the grid-cell networks
Tateisi science and technology fundation: 
Project Year: Oct 2018 - Jan 2019    Investigator(s): Yu Terada