33 citations · 52 across the 5 of their papers we have counts for
5 papers
SMKC: Sketch Based Kernel Correlation Images for Variable Cardinality Time Series Anomaly Detection
Haokun Zhou
Conventional anomaly detection in multivariate time series relies on the assumption that the set of observed variables remains static. In operational environments, however, monitor…
Concept drift of simple forecast models as a diagnostic of low-frequency, regime-dependent atmospheric reorganisation
Haokun Zhou
Data-driven weather prediction models implicitly assume that the statistical relationship between predictors and targets is stationary. Under anthropogenic climate change, this ass…
Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics
Hao Zhou, Sibo Cheng
Data-driven methods are emerging as efficient alternatives to traditional numerical forecasting, offering fast inference and lower computational cost. Yet, for complex systems, lon…
Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraint
Hanyang Wang, Hao Zhou, Sibo Cheng
Despite the success of various methods in addressing the issue of spatial reconstruction of dynamical systems with sparse observations, spatio-temporal prediction for sparse fields…
Multi-fidelity physics constrained neural networks for dynamical systems
Hao Zhou, Sibo Cheng, Rossella Arcucci
Physics-constrained neural networks are commonly employed to enhance prediction robustness compared to purely data-driven models, achieved through the inclusion of physical constra…