Local tensor-train surrogates approximate quantum machine learning models via Taylor polynomials and tensor networks, delivering polynomial parameter scaling and explicit generalization bounds controlled by patch radius.
Multidimensional fourier series with quantum circuits.Phys
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
quant-ph 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
A JAX-based framework extending quantum machine learning to pulse-level control with composable ansatzes, end-to-end optimization, and Fourier diagnostics.
citing papers explorer
-
Local tensor-train surrogates for quantum learning models
Local tensor-train surrogates approximate quantum machine learning models via Taylor polynomials and tensor networks, delivering polynomial parameter scaling and explicit generalization bounds controlled by patch radius.
-
Software Between Quantum and Machine Learning -- And Down to Pulses
A JAX-based framework extending quantum machine learning to pulse-level control with composable ansatzes, end-to-end optimization, and Fourier diagnostics.