108 citations · 125 across the 34 of their papers we have counts for
7 papers · 1 filter
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
Rikuto Kotoge, Zheng Chen, Tasuku Kimura +4
Dynamic GNNs, which integrate temporal and spatial features in Electroencephalography (EEG) data, have shown great potential in automating seizure detection. However, fully capturi…
Robust and Explainable Detector of Time Series Anomaly via Augmenting Multiclass Pseudo-Anomalies
Kohei Obata, Yasuko Matsubara, Yasushi Sakurai
Unsupervised anomaly detection in time series has been a pivotal research area for decades. Current mainstream approaches focus on learning normality, on the assumption that all or…
D-Tracker: Modeling Interest Diffusion in Social Activity Tensor Data Streams
Shingo Higashiguchi, Yasuko Matsubara, Koki Kawabata +2
Large quantities of social activity data, such as weekly web search volumes and the number of new infections with infectious diseases, reflect peoples' interests and activities. It…
CyberCScope: Mining Skewed Tensor Streams and Online Anomaly Detection in Cybersecurity Systems
Kota Nakamura, Koki Kawabata, Shungo Tanaka +2
Cybersecurity systems are continuously producing a huge number of time-stamped events in the form of high-order tensors, such as {count; time, port, flow duration, packet size, . .…
Modeling Time-evolving Causality over Data Streams
Naoki Chihara, Yasuko Matsubara, Ren Fujiwara +1
Given an extensive, semi-infinite collection of multivariate coevolving data sequences (e.g., sensor/web activity streams) whose observations influence each other, how can we disco…
ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
Rikuto Kotoge, Ziwei Yang, Zheng Chen +4
Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging task and often requires downstream anal…
Modeling Latent Non-Linear Dynamical System over Time Series
Ren Fujiwara, Yasuko Matsubara, Yasushi Sakurai
We study the problem of modeling a non-linear dynamical system when given a time series by deriving equations directly from the data. Despite the fact that time series data are giv…