59 citations · 167 across the 9 of their papers we have counts for
3 papers · 1 filter
Adaptive sampling-based optimization of quantics tensor trains for noisy functions: applications to quantum simulations
Kohtaroh Sakaue, Hiroshi Shinaoka, Rihito Sakurai
Tensor cross interpolation (TCI) is a powerful technique for learning a tensor train (TT) by adaptively sampling a target tensor based on an interpolation formula. However, when th…
Learning parameter dependence for Fourier-based option pricing with tensor trains
Rihito Sakurai, Haruto Takahashi, Koichi Miyamoto
A long-standing issue in mathematical finance is the speed-up of option pricing, especially for multi-asset options. A recent study has proposed to use tensor train learning algori…
Compactness of quantics tensor train representations of local imaginary-time propagators
Haruto Takahashi, Rihito Sakurai, Hiroshi Shinaoka
Space-time dependence of imaginary-time propagators, vital for \textit{ab initio} and many-body calculations based on quantum field theories, has been revealed to be compressible u…