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Yaqiong Li

2 accepted papers

2021

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks

ICML 2021spotlight

The Dirichlet Belief Network (DirBN) was recently proposed as a promising deep generative model to learn interpretable deep latent distributions for objects. However, its current representation capability is limited since its latent distributions across different layers is prone to form similar patt…

2020

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling

IJCAI 2020poster

The Dirichlet Belief Network~(DirBN) has been recently proposed as a promising approach in learning interpretable deep latent representations for objects. In this work, we leverage its interpretable modelling architecture and propose a deep dynamic probabilistic framework -- the Recurrent Dirichle…

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