117 citations · 340 across the 9 of their papers we have counts for
16 papers
Dequantizing quantum machine learning models using tensor networks
Seongwook Shin, Yong Siah Teo, Hyunseok Jeong
Ascertaining whether a classical model can efficiently replace a given quantum model -- dequantization -- is crucial in assessing the true potential of quantum algorithms. In this…
Exponential data encoding for quantum supervised learning
S. Shin, Y. S. Teo, H. Jeong
Reliable quantum supervised learning of a multivariate function mapping depends on the expressivity of the corresponding quantum circuit and measurement resources. We introduce exp…
Universal compressive tomography in the time-frequency domain
J. Gil-Lopez, Y. S. Teo, S. De +4
We implement a compressive quantum state tomography capable of reconstructing any arbitrary low-rank spectral-temporal optical signal with extremely few measurement settings and wi…
Emulation of quantum measurements with mixtures of coherent states
A. Mikhalychev, Y. S. Teo, H. Jeong +2
We propose a methodology to emulate quantum phenomena arising from any non-classical quantum state using only a finite set of mixtures of coherent states. This allows us to success…
Highly photon loss tolerant quantum computing using hybrid qubits
S. Omkar, Y. S. Teo, Seung-Woo Lee +1
We investigate a scheme for topological quantum computing using optical hybrid qubits and make an extensive comparison with previous all-optical schemes. We show that the photon lo…
Objective Compressive Quantum Process Tomography
Y. S. Teo, G. I. Struchalin, E. V. Kovlakov +6
We present a compressive quantum process tomography scheme that fully characterizes any rank-deficient completely-positive process with no a priori information about the process ap…