29 citations · 39 across the 4 of their papers we have counts for
4 papers
Time-series forecasting for nonlinear high-dimensional system using hybrid method combining autoencoder and multi-parallelized quantum long short-term memory and gated recurrent unit
Makoto Takagi, Ryuji Kokubo, Misato Kurosawa +7
A time-series forecasting method for high-dimensional spatial data is proposed. The method involves optimal selection of sparse sensor positions to efficiently represent the spatia…
Triple decomposition and sparse representation for noisy pressure-sensitive paint data
Koyo Kubota, Makoto Takagi, Tsubasa Ikami +5
Triple decomposition is a useful analytical method for extracting the mean value, organized coherent motion, and stochastic part from a fluctuating quantity. Although the pressure-…
Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology
Tomoki Inoue, Koyo Kubota, Tsubasa Ikami +5
Time-series clustering serves as a powerful data mining technique for time-series data in the absence of prior knowledge about clusters. A large amount of time-series data with lar…
Tackling the challenge of a huge materials science search space with quantum-inspired annealing
Kan Hatakeyama-Sato, Takahiro Kashikawa, Koichi Kimura +1
Efficient screening of chemicals is essential for exploring new materials. However, the search space is astronomically large, making calculations with conventional computers infeas…