Yuuji ICHISUGI

[Japanese]

National Institute of Advanced Industrial Science and Technology (AIST)

Research Papers (Computational Neuroscience and Artificial Intelligence)

Ichisugi Y., Takahashi N., Nakada H., Sano T.,
Hierarchical Reinforcement Learning with Unlimited Recursive Subroutine Calls. In Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, Lecture Notes in Computer Science, vol 11728, pp. 103--114, Springer, Cham, 2019.
[ paper ] [ slides ] [ Java program ]
Ichisugi Y., Takahashi N.,
A Formal Model of the Mechanism of Semantic Analysis in the Brain. In Proc. of Biologically Inspired Cognitive Architectures 2018 (BICA 2018), Advances in Intelligent Systems and Computing, vol 848. Springer, pp.128--137, 2018.
[ paper ] [ slides ] [ Prolog program ]
Takahashi N., Ichisugi Y.,
Toward Human-Like Sentence Interpretation -a Syntactic Parser Implemented as a Restricted Quasi Bayesian Network-, In Proc. of Biologically Inspired Cognitive Architectures 2018 (BICA 2018), Advances in Intelligent Systems and Computing, vol 848. Springer, pp.301--309, 2018.
[ paper ]
Hidemoto Nakada and Yuuji Ichisugi,
Context-Dependent Robust Text Recognition using Large-scale Restricted Bayesian Network, In Proc. of International Conference on Biologically Inspired Cognitive Architectures (BICA 2017), Procedia Computer Science, Vol. 123, pp.314--320, 2018.
[ paper ]
Naoto Takahashi and Yuuji Ichisugi,
Restricted Quasi Bayesian Networks as a Prototyping Tool for Computational Models of Individual Cortical Areas, In Proc. of Machine Learning Research (AMBN 2017), Proceedings of Machine Learning Research, Vol.73, pp.188--199, 2017.
[ paper ]
Takashi Sano and Yuuji Ichisugi,
Translation-Invariant Neural Responses as Variational Messages in a Bayesian Network Model, In Proc. of 26th International Conference on Artificial Neural Networks (ICANN 2017) Part I, Lecture Notes in Computer Science, Vol. 10613, pp.163--170, 2017.
[ paper ]
Yuuji Ichisugi,
Deep Restricted Bayesian Network BESOM,
5th Neuro Inspired Computational Elements Workshop (NICE 2017) [ slides ]
Yuuji Ichisugi and Takashi Sano,
Regularization Methods for the Restricted Bayesian Network BESOM,
In Proc. of International Conference on Neural Information Processing (ICONIP2016) Part I, LNCS 9947, pp.290--299, 2016.
[ paper ][ slides ]
Yuuji Ichisugi and Naoto Takahashi,
An Efficient Recognition Algorithm for Restricted Bayesian Networks,
2015 International Joint Conference on Neural Networks (IJCNN 2015).
[ paper ]
Yuuji Ichisugi, A Computational Model of Motor Areas Based on Bayesian Networks and Most Probable Explanations, In Proc. of The International Conference on Artificial Neural Networks (ICANN 2012), Part I, LNCS 7552, pp.726--733, 2012.
[ paper ]
Yuuji Ichisugi, "Recognition Model of Cerebral Cortex based on Approximate Belief Revision Algorithm", In Proc. of The 2011 International Joint Conference on Neural Networks (IJCNN 2011), pp.386--391, 2011.
[ paper ]
Yuuji Ichisugi, Haruo Hosoya, "Computational Model of the Cerebral Cortex that Performs Sparse Coding Using a Bayesian Network and Self-Organizing Maps", In Proc. of 17th International Conference on Neural Information Processing (ICONIP 2010), Part I, LNCS 6443, pp.33--40, Nov 2010.
[ paper ] [ slides ]
Yuuji Ichisugi, "A Neural Network Model of Cerebral Cortex that Combines Bayesian Network, SOM, ICA and Reinforcement Learning", In Proc. of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008), Organized Session, Sep 2008.
[ 20080715SCIS-ISIS.pdf ]
Yuuji ICHISUGI, "The cerebral cortex model that self-organizes conditional probability tables and executes belief propagation", In proc. of International Joint Conference on Neural Networks (IJCNN2007), Aug 2007.
[ paper ][ slides ]

Previous projects (Programming languages)

AIST home page.