1 citations · 1 across the 3 of their papers we have counts for
6 papers
Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings
Sebastian Cajas Ordóñez, Felipe Ocampo Osorio, Dax Enshan Koh +10
We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using quantum support vector machines (…
End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration
Xue Yang, Rigui Zhou, Shizheng Jia +5
Quantum Generative Adversarial Networks (QGANs) offer a promising path for learning data distributions on near-term quantum devices. However, existing QGANs for image synthesis avo…
Classical Shadows with Improved Median-of-Means Estimation
Winston Fu, Dax Enshan Koh, Siong Thye Goh +1
The classical shadows protocol, introduced by Huang et al. [Nat. Phys. 16, 1050 (2020)], makes use of the median-of-means (MoM) estimator to efficiently estimate the expectation va…
Quantum Volunteer's Dilemma
Dax Enshan Koh, Kaavya Kumar, Siong Thye Goh
The volunteer's dilemma is a well-known game in game theory that models the conflict players face when deciding whether to volunteer for a collective benefit, knowing that voluntee…
QROSS: QUBO Relaxation Parameter Optimisation via Learning Solver Surrogates
Tian Huang, Siong Thye Goh, Sabrish Gopalakrishnan +3
An increasingly popular method for solving a constrained combinatorial optimisation problem is to first convert it into a quadratic unconstrained binary optimisation (QUBO) problem…
A Minimax Surrogate Loss Approach to Conditional Difference Estimation
Siong Thye Goh, Cynthia Rudin
We present a new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework with binary outcomes. To overcome the problem th…