31 citations · 37 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…