4 papers
Problem-Specific Basis Quantum State Readout via Proper Orthogonal Decomposition
Kota Ichiki, Xinchi Huang, Gekko Budiutama +7
Quantum computing is a promising technology for accelerating partial differential equation solvers applied to large-scale real-world problems. However, reconstructing a classical r…
Approximate Amplitude Encoding with the Adaptive Interpolating Quantum Transform
Gekko Budiutama, Shunsuke Daimon, Xinchi Huang +2
Amplitude encoding of real-world data on quantum computers is often the workflow bottleneck: direct amplitude encoding scales poorly with input size and can offset any speedups in…
Adaptive Interpolating Quantum Transform: A Quantum-Native Framework for Efficient Transform Learning
Gekko Budiutama, Shunsuke Daimon, Hirofumi Nishi +3
Machine learning on quantum computers has attracted attention for its potential to deliver computational speedups in different tasks. However, deep variational quantum circuits req…
General Transform: A Unified Framework for Adaptive Transform to Enhance Representations
Gekko Budiutama, Shunsuke Daimon, Hirofumi Nishi +1
Discrete transforms, such as the discrete Fourier transform, are widely used in machine learning to improve model performance by extracting meaningful features. However, with numer…