36 citations · 91 across the 9 of their papers we have counts for
6 papers · 1 filter
Kriging and Gaussian processes: interconnected frameworks for spatial modelling and prediction
Hossein Mohammadi
Spatial modelling and inference arise across many areas of science and engineering, with Kriging and Gaussian process (GP) regression serving as two widely used predictive models.…
An ensemble-based approach for multi-fidelity emulation and adaptive sampling
Hossein Mohammadi
High-resolution simulation models are essential for representing complex physical systems, yet their substantial computational cost severely limits the number of feasible high-fide…
Cross-Validation Based Adaptive Sampling for Multi-Level Gaussian Process Models
Louise Kimpton, James Salter, Tim Dodwell +2
Complex computer codes or models can often be run in a hierarchy of different levels of complexity ranging from the very basic to the sophisticated. The top levels in this hierarch…
Sequential adaptive design for emulating costly computer codes
Hossein Mohammadi, Peter Challenor
Gaussian processes (GPs) are generally regarded as the gold standard surrogate model for emulating computationally expensive computer-based simulators. However, the problem of trai…
Emulating complex dynamical simulators with random Fourier features
Hossein Mohammadi, Peter Challenor, Marc Goodfellow
A Gaussian process (GP)-based methodology is proposed to emulate complex dynamical computer models (or simulators). The method relies on emulating the numerical flow map of the sys…
Emulating computer models with step-discontinuous outputs using Gaussian processes
Hossein Mohammadi, Peter Challenor, Marc Goodfellow +1
In many real-world applications we are interested in approximating costly functions that are analytically unknown, e.g. complex computer codes. An emulator provides a fast approxim…