activity
20162025
most citedThermodynamic evidence for nematic superconductivity in CuBiSe

273 citations · 289 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2025

LLM-Powered Fully Automated Chaos Engineering: Towards Enabling Anyone to Build Resilient Software Systems at Low Cost

Daisuke Kikuta, Hiroki Ikeuchi, Kengo Tajiri

Chaos Engineering (CE) is an engineering technique aimed at improving the resilience of distributed systems. It involves intentionally injecting faults into a system to test its re…

cs.SE2025

ChaosEater: Fully Automating Chaos Engineering with Large Language Models

Daisuke Kikuta, Hiroki Ikeuchi, Kengo Tajiri

Chaos Engineering (CE) is an engineering technique aimed at improving the resiliency of distributed systems. It involves artificially injecting specific failures into a distributed…

math.OC2024

Electric Vehicle Routing Problem for Emergency Power Supply: Towards Telecom Base Station Relief

Daisuke Kikuta, Hiroki Ikeuchi, Kengo Tajiri +3

As a telecom provider, our company has a critical mission to maintain telecom services even during power outages. To accomplish the mission, it is essential to maintain the power o…

cs.LG2024★ 7 cited

RouteExplainer: An Explanation Framework for Vehicle Routing Problem

Daisuke Kikuta, Hiroki Ikeuchi, Kengo Tajiri +1

The Vehicle Routing Problem (VRP) is a widely studied combinatorial optimization problem and has been applied to various practical problems. While the explainability for VRP is sig…

cs.NI2020

Dividing Deep Learning Model for Continuous Anomaly Detection of Inconsistent ICT Systems

Kengo Tajiri, Yasuhiro Ikeda, Yuusuke Nakano +1

Health monitoring is important for maintaining reliable information and communications technology (ICT) systems. Anomaly detection methods based on machine learning, which train a…

stat.ML2018★ 9 cited

Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders

Yasuhiro Ikeda, Kengo Tajiri, Yuusuke Nakano +2

Anomaly detection using dimensionality reduction has been an essential technique for monitoring multidimensional data. Although deep learning-based methods have been well studied f…

cond-mat.supr-con2016★ 273 cited

Thermodynamic evidence for nematic superconductivity in CuBiSe

Shingo Yonezawa, Kengo Tajiri, Suguru Nakata +5

Unconventional superconductivity is characterized by the spontaneous symmetry breaking of the macroscopic superconducting wavefunction in addition to the gauge symmetry breaking, s…