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20212024
most citedFock State-enhanced Expressivity of Quantum Machine Learning Models

31 citations · 37 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2024★ 1 cited

Concept learning of parameterized quantum models from limited measurements

Beng Yee Gan, Po-Wei Huang, Elies Gil-Fuster +1

Classical learning of the expectation values of observables for quantum states is a natural variant of learning quantum states or channels. While learning-theoretic frameworks esta…

cond-mat.mes-hall2024★ 4 cited

Measurement of enhanced spin-orbit coupling strength for donor-bound electron spins in silicon

Radha Krishnan, Beng Yee Gan, Yu-Ling Hsueh +6

While traditionally considered a deleterious effect in quantum dot spin qubits, the spin-orbit interaction is recently being revisited as it allows for rapid coherent control by on…

quant-ph2023★ 1 cited

A Unified Framework for Trace-induced Quantum Kernels

Beng Yee Gan, Daniel Leykam, Supanut Thanasilp

Quantum kernel methods are promising candidates for achieving a practical quantum advantage for certain machine learning tasks. Similar to classical machine learning, an exact form…

quant-ph2023

Landscape approximation of low energy solutions to binary optimization problems

Benjamin Y. L. Tan, Beng Yee Gan, Daniel Leykam +1

We show how the localization landscape, originally introduced to bound low energy eigenstates of disordered wave media and many-body quantum systems, can form the basis for hardwar…

quant-ph2021★ 31 cited

Fock State-enhanced Expressivity of Quantum Machine Learning Models

Beng Yee Gan, Daniel Leykam, Dimitris G. Angelakis

The data-embedding process is one of the bottlenecks of quantum machine learning, potentially negating any quantum speedups. In light of this, more effective data-encoding strategi…