2 citations · 3 across the 6 of their papers we have counts for
6 papers
Quantum Statistical Memory Advantage Reveals Predictive Structure in Chaotic Invariant Measures
Maida Wang, Xiao Xue, Minh Chung +1
Long-horizon prediction of a chaotic system is governed by fidelity to its invariant measure, and which parts of that measure a learned predictor needs is a physical question not k…
Explainable quantum-compressed machine learning for complex fluid flows
Xiao Xue, Maida Wang, Mingyang Gao +2
Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep…
Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows
Xiao Xue, Tianyue Yang, Mingyang Gao +7
Spatiotemporal flows govern diverse phenomena across physics, biology, and engineering, yet modelling their multiscale dynamics remains a central challenge. Despite major advances…
Q-BAR: Blogger Anomaly Recognition via Quantum-enhanced Manifold Learning
Maida Wang, Panyun Jiang
In recommendation-driven online media, creators increasingly suffer from semantic mutation, where malicious secondary edits preserve visual fidelity while altering the intended mea…
Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage
Maida Wang, Xiao Xue, Mingyang Gao +1
We introduce a quantum-informed machine learning (QIML) framework for modelling the long-term behaviour of high-dimensional chaotic systems. QIML combines a one-time, offline-train…
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor
Maida Wang, Jinyang Jiang, Peter V. Coveney
Quantum machine learning has gained attention for its potential to address computational challenges. However, whether those algorithms can effectively solve practical problems and…