8 citations · 22 across the 10 of their papers we have counts for
10 papers
Signature Isolation Forest
Marta Campi, Guillaume Staerman, Gareth W. Peters +1
Functional Isolation Forest (FIF) is a recent state-of-the-art Anomaly Detection (AD) algorithm designed for functional data. It relies on a tree partition procedure where an abnor…
Data-Driven Framework for Uncovering Hidden Control Strategies in Evolutionary Analysis
Nourddine Azzaoui, Tomoko Matsui, Daisuke Murakami
We have devised a data-driven framework for uncovering hidden control strategies used by an evolutionary system described by an evolutionary probability distribution. This innovati…
-algebra Net: A New Approach Generalizing Neural Network Parameters to -algebra
Yuka Hashimoto, Zhao Wang, Tomoko Matsui
We propose a new framework that generalizes the parameters of neural network models to -algebra-valued ones. -algebra is a generalization of the space of complex numbers.…
Impact of COVID-19 type events on the economy and climate under the stochastic DICE model
Pavel V. Shevchenko, Daisuke Murakami, Tomoko Matsui +1
The classical DICE model is a widely accepted integrated assessment model for the joint modeling of economic and climate systems, where all model state variables evolve over time d…
Tweet Analysis for Enhancement of COVID-19 Epidemic Simulation: A Case Study in Japan
Vu Tran, Tomoko Matsui
The COVID-19 pandemic, which began in December 2019, progressed in a complicated manner and thus caused problems worldwide. Seeking clues to the reasons for the complicated progres…
Analysis of COVID-19 evolution based on testing closeness of sequential data
Tomoko Matsui, Nourddine Azzaoui, Daisuke Murakami
A practical algorithm has been developed for closeness analysis of sequential data that combines closeness testing with algorithms based on the Markov chain tester. It was applied…
Improved log-Gaussian approximation for over-dispersed Poisson regression: application to spatial analysis of COVID-19
Daisuke Murakami, Tomoko Matsui
In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiabili…
Compositionally-warped additive mixed modeling for a wide variety of non-Gaussian spatial data
Daisuke Murakami, Mami Kajita, Seiji Kajita +1
As with the advancement of geographical information systems, non-Gaussian spatial data sets are getting larger and more diverse. This study develops a general framework for fast an…
Spatiotemporal analysis of urban heatwaves using Tukey g-and-h random field models
Daisuke Murakami, Gareth W. Peters, Tomoko Matsui +1
The statistical quantification of temperature processes for the analysis of urban heat island (UHI) effects and local heat-waves is an increasingly important application domain in…
A spatiotemporal analysis of participatory sensing data "tweets" and extreme climate events toward real-time urban risk management
Yoshiki Yamagata, Daisuke Murakami, Gareth W. Peters +1
Real-time urban climate monitoring provides useful information that can be utilized to help monitor and adapt to extreme events, including urban heatwaves. Typical approaches to th…