Team leaderMasaaki Imaizumi
The High-Dimensional Causal Analysis Team studies the causal structure in high-dimensional data. In today's world of advanced data acquisition, storage, and analysis technologies, not only the structures possessed by data, but also the data science techniques for analyzing them have become highly complex. This team aims to understand both the large-degree-of-freedom, high-dimensional, and complex structures of data and the techniques for analyzing them, and to construct and extend theories based on these understandings. As specific methodologies, we study modern high-dimensional statistics and deep learning theory, and use them to develop methods of analysis and statistical inference for causal structures.