3 citations · 4 across the 9 of their papers we have counts for
9 papers
Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies
Takuro Kutsuna, Noriko N. Ishizaki, Norihiro Oyama +1
Physics-based climate projections using general circulation models are essential for assessing future risks, but their coarse resolution limits regional decision-making. Statistica…
Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study
Yuki Chiba, Norikazu Saito, Yuki Ueda +1
Recent empirical studies have reported that spatiotemporal congestion clusters in urban traffic exhibit scale-free statistics, with cluster size following a power-law distribution.…
Traffic signal optimization in large-scale urban road networks: an adaptive-predictive controller using Ising models
Daisuke Inoue, Hiroshi Yamashita, Kazuyuki Aihara +1
Realizing smooth traffic flow is important for achieving carbon neutrality. Adaptive traffic signal control, which considers traffic conditions, has thus attracted attention. Howev…
Predicting unobserved climate time series data at distant areas via spatial correlation using reservoir computing
Shihori Koyama, Daisuke Inoue, Hiroaki Yoshida +2
Collecting time series data spatially distributed in many locations is often important for analyzing climate change and its impacts on ecosystems. However, comprehensive spatial da…
An Uncertainty-aware, Mesh-free Numerical Method for Kolmogorov PDEs
Daisuke Inoue, Yuji Ito, Takahito Kashiwabara +2
This study introduces an uncertainty-aware, mesh-free numerical method for solving Kolmogorov PDEs. In the proposed method, we use Gaussian process regression (GPR) to smoothly int…
Convergence Analysis of the Upwind Difference Methods for Hamilton-Jacobi-Bellman Equations
Daisuke Inoue, Yuji Ito, Takahito Kashiwabara +2
This paper investigates the convergence properties of the upwind difference scheme for the Hamilton--Jacobi--Bellman (HJB) equation, a central partial differential equation in opti…
Dynamical cooperation model for mitigating the segregation phase in Schelling's model
Akihisa Okada, Daisuke Inoue, Shihori Koyama +2
We consider a Schelling-like segregation model, in which the behavior of individual agents is determined by a mixed individual and global utility. With a high ratio of global utili…
A fictitious-play finite-difference method for linearly solvable mean field games
Daisuke Inoue, Yuji Ito, Takahito Kashiwabara +2
An iterative finite difference scheme for mean field games (MFGs) is proposed. The target MFGs are derived from control problems for multidimensional systems with advection terms.…
Model Predictive Mean Field Games for Controlling Multi-Agent Systems
Daisuke Inoue, Yuji Ito, Takahito Kashiwabara +2
When controlling multi-agent systems, the trade-off between performance and scalability is a major challenge. Here, we address this difficulty by using mean field games (MFGs), whi…