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Serket is a library for constructing large-scale models and estimating their parameters via the connection of the modules. You can use the following probabilistic models and neural network models:

Serket makes it possible to construct large-scale models by connecting these modules.



The concept of Serket is described in the following paper:

title={SERKET: An Architecture For Connecting Stochastic Models to Realize a Large-Scale Cognitive Model},
author={Nakamura, Tomoaki and Nagai, Takayuki and Taniguchi, Tadahiro},
journal={Frontiers in Neurorobotics},

We have also published a Japanese paper describing some of the modules:

國安瞭,中村友昭,青木達哉,谷口彰,尾崎僚,伊志嶺朝良,横山裕樹,小椋忠志,長井隆行,谷口忠大,”確率モデルの統合による大規模なモデルの実現 ~VAE, GMM, HMM, MLDAの統合モデルの実装と評価~”,情報論的学習理論ワークショップ,T-34,Nov. 2018
國安瞭,中村友昭,長井隆行,谷口忠大,”確率モデルの統合によるマルチモーダル学習モデルの構築”,人工知能学会全国大会,1L4-J-11-02,Jun. 2019