Our main research goal is to develop a better understanding on

how deep learning works, especially from the view point of representation learning.

Our research scope covers a variety of topics in deep learning

including unsupervised learning, information theoretic approaches,

representation learning, representations of transformers, interpretation of representations, meta-learning, NAS, structured compression of DNN, etc.