Dynamic Multi-Network Mining of Tensor Time Series

1 code implementation • 19 Feb 2024 • Kohei Obata, Koki Kawabata, Yasuko Matsubara, Yasushi Sakurai

(a) Interpretable: it characterizes the cluster with multiple networks, each of which is a sparse dependency network of a corresponding non-temporal mode, and thus provides visible and interpretable insights into the key relationships.

Clustering Time Series

MoCLIM: Towards Accurate Cancer Subtyping via Multi-Omics Contrastive Learning with Omics-Inference Modeling

no code implementations • 17 Aug 2023 • Ziwei Yang, Zheng Chen, Yasuko Matsubara, Yasushi Sakurai

Precision medicine fundamentally aims to establish causality between dysregulated biochemical mechanisms and cancer subtypes.

Contrastive Learning Representation Learning

Fast and Multi-aspect Mining of Complex Time-stamped Event Streams

2 code implementations • 7 Mar 2023 • Kota Nakamura, Yasuko Matsubara, Koki Kawabata, Yuhei Umeda, Yuichiro Wada, Yasushi Sakurai

Thanks to its concise but effective summarization, CubeScope can also detect the sudden appearance of anomalies and identify the types of anomalies that occur in practice.

Anomaly Detection Data Compression

Mining Reaction and Diffusion Dynamics in Social Activities

no code implementations • 7 Aug 2022 • Taichi Murayama, Yasuko Matsubara, Yasushi Sakurai

Large quantifies of online user activity data, such as weekly web search volumes, which co-evolve with the mutual influence of several queries and locations, serve as an important social sensor.